A maize WAK-SnRK1α2-WRKY module regulates nutrient availability to defend against head smut disease.

Obligate biotrophs depend on living hosts for nutrient acquisition to complete their life cycle, yet the mechanisms by which hosts restrict nutrient availability to pathogens remain largely unknown. The fungal pathogen Sporisorium reilianum infects maize seedlings and causes head smut disease in inflorescences at maturity, while a cell wall-associated kinase, ZmWAK, provides quantitative resistance against it. In this study, we demonstrate that S. reilianum can rapidly activate ZmWAK kinase activity, which is sustained by the 407th threonine residue in the juxtamembrane domain, enabling it to interact with and phosphorylate ZmSnRK1α2, a conserved sucrose non-fermenting-related kinase α subunit. The activated ZmSnRK1α2 translocates from the cytoplasm to the nucleus, where it phosphorylates and destabilizes the transcription factor ZmWRKY53. The reduced ZmWRKY53 abundance leads to the downregulation of genes involved in transmembrane transport and carbohydrate metabolism, resulting in nutrient starvation for S. reilianum in the apoplast. Collectively, our study uncovers a WAK-SnRK1α2-WRKY53 signaling module in maize that conveys phosphorylation cascades from the plasma membrane to the nucleus to confer plant resistance against head smut in maize, offering new insights and potential targets for crop disease management.

Noise Self-Regression: A New Learning Paradigm to Enhance Low-Light Images Without Task-Related Data.

Deep learning-based low-light image enhancement (LLIE) is a task of leveraging deep neural networks to enhance the image illumination while keeping the image content unchanged. From the perspective of training data, existing methods complete the LLIE task driven by one of the following three data types: paired data, unpaired data and zero-reference data. Each type of these data-driven methods has its own advantages, e.g., zero-reference data-based methods have very low requirements on training data and can meet the human needs in many scenarios. In this paper, we leverage pure Gaussian noise to complete the LLIE task, which further reduces the requirements for training data in LLIE tasks and can be used as another alternative in practical use. Specifically, we propose Noise SElf-Regression (NoiSER) without access to any task-related data, simply learns a convolutional neural network equipped with an instance-normalization layer by taking a random noise image, N(0,σ2) for each pixel, as both input and output for each training pair, and then the low-light image is fed to the trained network for predicting the normal-light image. Technically, an intuitive explanation for its effectiveness is as follows: 1) the self-regression reconstructs the contrast between adjacent pixels of the input image, 2) the instance-normalization layer may naturally remediate the overall magnitude/lighting of the input image, and 3) the N(0,σ2) assumption for each pixel enforces the output image to follow the well-known gray-world hypothesis [1] when the image size is big enough. Compared to current state-of-the-art LLIE methods with access to different task-related data, NoiSER is highly competitive in enhancement quality, yet with a much smaller model size, and much lower training and inference cost. In addition, the experiments also demonstrate that NoiSER has great potential in overexposure suppression and joint processing with other restoration tasks.

Natural variations of maize ZmLecRK1 determine its interaction with ZmBAK1 and resistance patterns to multiple pathogens.

Maize (Zea mays) is one of the most important crops in the world, but its yield and quality are seriously affected by diverse diseases. Identifying broad-spectrum resistance genes is crucial for developing effective strategies to control the disease in maize. In a genome-wide study in maize, we identified a G-type lectin receptor kinase ZmLecRK1, as a new resistance protein against Pythium aphanidermatum, one of the causal pathogens of stalk rot in maize. Genetic analysis showed that the specific ZmLecRK1 allele can confer resistance to multiple pathogens in maize. The cell death and disease resistance phenotype mediated by the resistant variant of ZmLecRK1 requires the co-receptor ZmBAK1. A naturally occurring A404S variant in the extracellular domain of ZmLecRK1 determines the ZmLecRK1-ZmBAK1 interaction and the formation of ZmLecRK1-related protein complexes. Interestingly, the ZmLecRK1 susceptible variant was found to possess the amino acid S404 that is present in the ancestral variants of ZmLecRK1 and conserved among the majority of grass species, while the resistance variant of ZmLecRK1 with A404 is only present in a few maize inbred lines. Substitution of S by A at position 404 in ZmLecRK1-like proteins of sorghum and rice greatly enhances their ability to induce cell death. Further transcriptomic analysis reveals that ZmLecRK1 likely regulates gene expression related to the pathways in cell wall organization or biogenesis in response to pathogen infection. Taken together, these results suggest that the ZmLecRK1 resistance variant enhances its binding affinity to the co-receptor ZmBAK1, thereby enhancing the formation of active complexes for defense in maize. Our work highlights the biotechnological potential for generating disease-resistant crops by precisely modulating the activity of ZmLecRK1 and its homologs through targeted base editing.

The maize ZmCPK39-ZmKnox2 module regulates plant height.

Plant height is an important agronomic trait that affects high-density tolerance and lodging resistance. However, the regulators and their underlying molecular mechanisms controlling plant height in maize remain understudied. Here, we report that knockout mutants of the calcium-dependent protein kinase gene ZmCPK39 (ZmCPK39-KO) exhibit dramatically reduced plant height, characterized by shorter internodes and a slight decrease in node numbers. Furthermore, we identified a ZmCPK39-interacting protein, the knotted-related homeobox (ZmKnox2), and observed that plant height was also significantly reduced in a mutator transposon-inserted mutant of ZmKnox2 (ZmKnox2-Mu). Combined analysis of transcriptomic and metabonomic data indicates that multiple phytohormone signaling and photosynthesis pathways are disrupted in both ZmCPK39-KO and ZmKnox2-Mu mutants. Taken together, these results provide new insights into the function of ZmCPK39 and identify potential targets for breeding lodging-resistant and high-density tolerant maize cultivars. Supplementary Information: The online version contains supplementary material available at 10.1007/s42994-024-00150-y.

The Potential Role of Artemisinins Against Neurodegenerative Diseases.

Artemisinin (ART) and its derivatives, collectively referred to as artemisinins (ARTs), have been approved for the treatment of malaria for decades. ARTs are converted into dihydroartemisinin (DHA), the only active form, which is reductive in vivo. In this review, we provide a brief overview of the neuroprotective potential of ARTs and the underlying mechanisms on several of the most common neurodegenerative diseases, particularly considering their potential application in those associated with cognitive and motor impairments including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS). ARTs act as autophagy balancers to alleviate AD and PD. They inhibit neuroinflammatory responses by regulating phosphorylation of signal transduction proteins, such as AKT, PI3K, ERK, NF-[Formula: see text]B, p38 MAPK, I[Formula: see text]B[Formula: see text]. In addition, ARTs regulate GABAergic signaling in a dose-dependent manner. Although they competitively inhibit the binding of gephyrin to GABAergic receptors, low doses of ARTs enhance GABAergic signaling. ARTs can also inhibit ferroptosis, activate the Akt/Bcl-2, AMPK, or ERK/CREB pathways to reduce oxidative stress, and maintain mitochondrial homeostasis, protecting neurons from oxidative stress injury. More importantly, ARTs structurally combine with and suppress [Formula: see text]-Amyloid (A[Formula: see text]-induced neurotoxicity, reduce P-tau, and maintain O-GlcNAcylation/Phosphorylation balance, leading to relieved pathological changes in neurodegenerative diseases. Collectively, these natural properties endow ARTs with unique potential for application in neurodegenerative diseases.

ZmGDIα-hel counters the RBSDV-induced reduction of active gibberellins to alleviate maize rough dwarf virus disease.

Maize rough dwarf disease (MRDD) threatens maize production globally. The P7-1 effector of the rice black-streaked dwarf virus (RBSDV) targets maize Rab GDP dissociation inhibitor alpha (ZmGDIα) to cause MRDD. However, P7-1 has difficulty recruiting a ZmGDIα variant with an alternative helitron-derived exon 10 (ZmGDIα-hel), resulting in recessive resistance. Here, we demonstrate that P7-1 can recruit another maize protein, gibberellin 2-oxidase 13 (ZmGA2ox7.3), which also exhibits tighter binding affinity for ZmGDIα than ZmGDIα-hel. The oligomerization of ZmGA2ox7.3 is vital for its function in converting bioactive gibberellins into inactive forms. Moreover, the enzymatic activity of ZmGA2ox7.3 oligomers increases when forming hetero-oligomers with P7-1/ZmGDIα, but decreases when ZmGDIα-hel replaces ZmGDIα. Viral infection significantly promotes ZmGA2ox7.3 expression and oligomerization in ZmGDIα-containing susceptible maize, resulting in reduced bioactive GA1/GA4 levels. This causes an auxin/cytokinin imbalance and ultimately manifests as MRDD syndrome. Conversely, in resistant maize, ZmGDIα-hel counters these virus-induced changes, thereby mitigating MRDD severity.

[Ilizarov technique combined with center of rotation dome-shaped osteotomy for the treatment of juvenile distal femoral valgus deformity].

OBJECTIVE: To investigate the effect of Ilizarov technique combined with rotational center dome-shaped osteotomy in the treatment of juvenile distal femoral valgus deformity. METHODS: A retrospective study was conducted to analyze the clinical data of 11 patients with valgus deformity of the distal femur who had been admitted and followed up completely from January 2016 to October 2020. There were 7 males and 4 females. The 6 patients were on the right side and 5 patients were on the left side. The age ranged from 10 to 14 years old. The center of roration of angulation(CORA) was identified at the distal femur deformity, and dome-shaped osteotomy was performed with the CORA as the midpoint. The annular external fixator was installed according to the needle threading principle of Ilizarov external fixation, and the distal femur was cut off. The valgus deformity under visual inspection of the distal femur was corrected immediately, and the external fixator was fixed and maintained. The residual deformity and shortening were corrected according to the force line and length of the lower limbs suggested by the weight-bearing full-length anteroposterior and lateral X-rays of both lower limbs. RESULTS: All 11 patients were followed up for 13 to 25 months. The time of wearing external fixator was 12 to 17 weeks. In the last follow-up, both lower limbs were measured by the weight-bearing full-length anteroposterior and lateral X-rays, and the length of both lower limbs of 11 patients were equal, and the deformities were corrected. The score of hospital for special surgery (HSS) was used to evaluate the knee function, all of which were excellent. CONCLUSION: The Ilizarov technique was applied in the treatment of distal femoral valgus deformity in adolescents using a rotating central dome-shaped osteotomy. Visual femoral valgus deformity was corrected immediately during the operation. After the operation, residual deformities and shortening were dynamically adjusted and corrected according to the force line and shortening degree of lower extremities indicated by the weight-bearing anteroposterior and lateral radiographs of both lower limbs, with minimal damage and fast recovery.

Proxitome profiling reveals a conserved SGT1-NSL1 signaling module that activates NLR-mediated immunity.

Suppressor of G2 allele of skp1 (SGT1) is a highly conserved eukaryotic protein that plays a vital role in growth, development, and immunity in both animals and plants. Although some SGT1 interactors have been identified, the molecular regulatory network of SGT1 remains unclear. SGT1 serves as a co-chaperone to stabilize protein complexes such as the nucleotide-binding leucine-rich repeat (NLR) class of immune receptors, thereby positively regulating plant immunity. SGT1 has also been found to be associated with the SKP1-Cullin-F-box (SCF) E3 ubiquitin ligase complex. However, whether SGT1 targets immune repressors to coordinate plant immune activation remains elusive. In this study, we constructed a toolbox for TurboID- and split-TurboID-based proximity labeling (PL) assays in Nicotiana benthamiana and used the PL toolbox to explore the SGT1 interactome during pre- and post-immune activation. The comprehensive SGT1 interactome network we identified highlights a dynamic shift from proteins associated with plant development to those linked with plant immune responses. We found that SGT1 interacts with Necrotic Spotted Lesion 1 (NSL1), which negatively regulates salicylic acid-mediated defense by interfering with the nucleocytoplasmic trafficking of non-expressor of pathogenesis-related genes 1 (NPR1) during N NLR-mediated response to tobacco mosaic virus. SGT1 promotes the SCF-dependent degradation of NSL1 to facilitate immune activation, while salicylate-induced protein kinase-mediated phosphorylation of SGT1 further potentiates this process. Besides N NLR, NSL1 also functions in several other NLR-mediated immunity. Collectively, our study unveils the regulatory landscape of SGT1 and reveals a novel SGT1-NSL1 signaling module that orchestrates plant innate immunity.

Dihydroartemisinin promotes tau O-GlcNAcylation and improves cognitive function in hTau transgenic mice.

Tauopathy is a collective term for several neurodegenerative diseases characterized by the intracellular accumulation of hyperphosphorylated microtubule-associated protein Tau (P-tau). Our recent report has revealed the neuroprotective effect of dihydroartemisinin (DHA) on mice overexpressing human Tau (hTau) in the hippocampus by enhancing O-linked-N-Acetylglucosaminylation (O-GlcNAcylation) modification. However, whether DHA can improve synaptic and cognitive function in hTau transgenic mice by specifically promoting Tau O-GlcNAcylation is still unclear. Here, we introduced hTau transgenic mice, a more optimal tauopathy model, to study the effect of DHA on Tau O-GlcNAcylation. We reported that DHA treatment alleviated the deficits of hippocampal CA1 LTP and spatial learning and memory in the Barnes maze and context fear conditioning tests in hTau transgenic mice. Mechanically, we revealed that DHA exerted a significant protective effect by upregulating Tau O-GlcNAcylation and attenuating Tau hyperphosphorylation. Through molecular docking, we found a stable binding between DHA and O-GlcNAc transferase (OGT). We further reported that DHA treatment had no effect on the expression of OGT, but it promoted OGT nuclear export, thereby enhancing OGT-mediated Tau O-GlcNAcylation. Taken together, these results indicate that DHA exerts neuroprotective effect by promoting cytoplasmic translocation of OGT and rebuilding the balance of Tau O-GlcNAcylation/phosphorylation, enhancing O-GlcNAcylation of Tau, suggesting that DHA may be a potential therapeutic agent against tauopathy.

Time-gated imaging through dense fog via physics-driven Swin transformer.

Imaging through the fog is valuable for many areas, such as autonomous driving and cosmic exploration. However, due to the influence of strong backscattering and diffuse reflection generated by the dense fog on the temporal-spatial correlations of photons returning from the target object, the reconstruction quality of most existing methods is significantly reduced under dense fog conditions. In this study, we describe the optical scatter imaging process and propose a physics-driven Swin Transformer method utilizing Time-of-Flight (ToF) and Deep Learning principles to mitigate scattering effects and reconstruct targets in conditions of heterogeneous dense fog. The results suggest that, despite the exponential decrease in the number of ballistic photons as the optical thickness of fog increases, the Physics-Driven Swin Transformer method demonstrates satisfactory performance in imaging targets obscured by dense fog. Importantly, this article highlights that even in dense fog imaging experiments with optical thickness reaching up to 3.0, which exceeds previous studies, commonly utilized quantitative evaluation metrics like PSNR and SSIM indicate that our method is cutting-edge in imaging through dense fog.

SNIL: Generating Sports News From Insights With Large Language Models.

To enhance the appeal and informativeness of data news, there is an increasing reliance on data analysis techniques and visualizations, which poses a high demand for journalists' abilities. While numerous visual analytics systems have been developed for deriving insights, few tools specifically support and disseminate viewpoints for journalism. Thus, this work aims to facilitate the automatic creation of sports news from natural language insights. To achieve this, we conducted an extensive preliminary study on the published sports articles. Based on our findings, we propose a workflow - 1) exploring the data space behind insights, 2) generating narrative structures, 3) progressively generating each episode, and 4) mapping data spaces into communicative visualizations. We have implemented a human-AI interaction system called SNIL, which incorporates user input in conjunction with large language models (LLMs). It supports the modification of textual and graphical content within the episode-based structure by adjusting the description. We conduct user studies to demonstrate the usability of SNIL and the benefit of bridging the gap between analysis tasks and communicative tasks through expert and fan feedback.

MNTZNN for Solving Hybrid Double-Deck Dynamic Nonlinear Equation System Applied to Robot Manipulator Control.

Compared with conventional dynamic nonlinear equation systems, a hybrid double-deck dynamic nonlinear equation system (H3DNES) not only has multiple layers describing more different tasks in practice, but also has a hybrid nonlinear structure of solution and its derivative describing their nonlinear constraints. Its characteristics lead to the ability to describe more complicated problems involving multiple constraints, and strong nonlinear and dynamic features, such as robot manipulator tracking control. Besides, noises are inevitable in practice and thus strong robustness of models solving H3DNES is also necessary. In this work, a multilayered noise-tolerant zeroing neural network (MNTZNN) model is proposed for solving H3DNES. MNTZNN model has strong robustness and it solves H3DNES successfully even when noises exist in both the two layers of H3DNES. In order to develop the MNTZNN model, a new zeroing neural network (ZNN) design formula is proposed. It not only enables equations with respect to solutions to become equations with respect to the second-order derivatives of solutions but also makes the corresponding model have strong robustness. The robustness of the MNTZNN model is proved when parameters in the model satisfy a loose constraint and the error bounds are programmable via setting appropriate parameter values. Finally, the MNTZNN model is applied to the tracking control of the six-link planar robot manipulator and PUMA560 robot manipulator with hybrid nonlinear constraints of joint angle and velocity.

PCSK6 exacerbates Alzheimer's disease pathogenesis by promoting MT5-MMP maturation.

Proprotein convertase subtilisin/kexin type 6 (PCSK6) is a calcium-dependent serine proteinase that regulates the proteolytic activity of various precursor proteins and facilitates protein maturation. Dysregulation of PCSK6 expression or function has been implicated in several pathological processes including nervous system diseases. However, whether and how PCSK6 is involved in the pathogenesis of Alzheimer's disease (AD) remains unclear. In this study, we reported that the expression of PCSK6 was significantly increased in the brain tissues of postmortem AD patients and APP23/PS45 transgenic AD model mice, as well as N2AAPP cells. Genetic knockdown of PCSK6 reduced amyloidogenic processing of APP in N2AAPP cells by suppressing the activation of membrane-type 5-matrix metalloproteinase (MT5-MMP), referred to as η-secretase. We further found that PCSK6 cleaved and activated MT5-MMP by recognizing the RRRNKR sequence in its N-terminal propeptide domain in N2A cells. The mutation or knockout of this cleavage motif prevented PCSK6 from interacting with MT5-MMP and performing cleavage. Importantly, genetic knockdown of PCSK6 with adeno-associated virus (AAV) reduced Aß production and ameliorated hippocampal long-term potentiation (LTP) and long-term spatial learning and memory in APP23/PS45 transgenic mice. Taken together, these results demonstrate that genetic knockdown of PCSK6 effectively alleviate AD-related pathology and cognitive impairments by inactivating MT5-MMP, highlighting its potential as a novel therapeutic target for AD treatment.

The ZmWAKL-ZmWIK-ZmBLK1-ZmRBOH4 module provides quantitative resistance to gray leaf spot in maize.

Gray leaf spot (GLS), caused by the fungal pathogens Cercospora zeae-maydis and Cercospora zeina, is a major foliar disease of maize worldwide (Zea mays L.). Here we demonstrate that ZmWAKL encoding cell-wall-associated receptor kinase-like protein is the causative gene at the major quantitative disease resistance locus against GLS. The ZmWAKLY protein, encoded by the resistance allele, can self-associate and interact with a leucine-rich repeat immune-related kinase ZmWIK on the plasma membrane. The ZmWAKLY/ZmWIK receptor complex interacts with and phosphorylates the receptor-like cytoplasmic kinase (RLCK) ZmBLK1, which in turn phosphorylates its downstream NADPH oxidase ZmRBOH4. Upon pathogen infection, ZmWAKLY phosphorylation activity is transiently increased, initiating immune signaling from ZmWAKLY, ZmWIK, ZmBLK1 to ZmRBOH4, ultimately triggering a reactive oxygen species burst. Our study thus uncovers the role of the maize ZmWAKL-ZmWIK-ZmBLK1-ZmRBOH4 receptor/signaling/executor module in perceiving the pathogen invasion, transducing immune signals, activating defense responses and conferring increased resistance to GLS.

Arthroscopy-assisted reduction and simultaneous robotic-assisted screw placement in the treatment of fractures of the posterior talar process.

PURPOSE: A fracture of the posterior talar process is easily missed because of its hidden position. Inappropriate treatment is likely to result in complications, such as nonunion of the fracture and traumatic arthritis. This study evaluated the outcomes of arthroscopy-assisted reduction combined with robotic-assisted screw placement in the treatment of fractures of the posterior talar process. METHODS: The clinical data for nine patients who underwent surgical treatment of a fracture of the posterior talar process at our institution between September 2017 and January 2021 were retrospectively reviewed. Arthroscopy-assisted reduction of the fracture was performed, and a cannulated screw was placed using three-dimensional orthopedic robotic-assisted navigation. RESULTS: The patients (seven men, two women) had a mean age of 36.33 ± 9.77 years and were followed up for 21 ± 5.43 months. The operation time was 106.67 ± 24.5 min with blood loss of 47.78 ± 9.05 ml. Primary healing was obtained in all cases, and no patient sustained a nerve or tendon injury, had fracture nonunion, or developed talar osteonecrosis. One patient developed subtalar arthritis, for which subtalar joint fusion was performed; pain was markedly less severe after cleaning. CONCLUSION: Arthroscopy-assisted reduction and robotic-assisted screw placement have the advantages of visualization of fracture reduction, minimal injury, and precise screw placement in the treatment of fractures of the posterior talar process.

Visualizing Large-Scale Spatial Time Series with GeoChron.

In geo-related fields such as urban informatics, atmospheric science, and geography, large-scale spatial time (ST) series (i.e., geo-referred time series) are collected for monitoring and understanding important spatiotemporal phenomena. ST series visualization is an effective means of understanding the data and reviewing spatiotemporal phenomena, which is a prerequisite for in-depth data analysis. However, visualizing these series is challenging due to their large scales, inherent dynamics, and spatiotemporal nature. In this study, we introduce the notion of patterns of evolution in ST series. Each evolution pattern is characterized by 1) a set of ST series that are close in space and 2) a time period when the trends of these ST series are correlated. We then leverage Storyline techniques by considering an analogy between evolution patterns and sessions, and finally design a novel visualization called GeoChron, which is capable of visualizing large-scale ST series in an evolution pattern-aware and narrative-preserving manner. GeoChron includes a mining framework to extract evolution patterns and two-level visualizations to enhance its visual scalability. We evaluate GeoChron with two case studies, an informal user study, an ablation study, parameter analysis, and running time analysis.

The maize transcription factor CCT regulates drought tolerance by interacting with Fra a 1, E3 ligase WIPF2, and auxin response factor Aux/IAA8.

Plants are commonly exposed to abiotic stressors, which can affect their growth, productivity, and quality. Previously, the maize transcription factor ZmCCT was shown to be involved in the photoperiod response, delayed flowering, and quantitative resistance to Gibberella stalk rot. In this study, we demonstrate that ZmCCT can regulate plant responses to drought. ZmCCT physically interacted with ZmFra a 1, ZmWIPF2, and ZmAux/IAA8, which localized to the cell membrane, cytoplasm, and nucleus, respectively, both in vitro and in vivo in a yeast two-hybrid screen in response to abiotic stress. Notably, ZmCCT recruits ZmWIPF2 to the nucleus, which has strong E3 self-ubiquitination activity dependent on its RING-H2 finger domain in vitro. When treated with higher indole-3-acetic acid/abscisic acid ratios, the height and root length of Y331-ΔTE maize plants increased. Y331-ΔTE plants exhibited increased responses to exogenously applied auxin or ABA compared to Y331 plants, indicating that ZmCCT may be a negative regulator of ABA signalling in maize. In vivo, ZmCCT promoted indole-3-acetic acid biosynthesis in ZmCCT-overexpressing Arabidopsis. RNA-sequencing and DNA affinity purification-sequencing analyses showed that ZmCCT can regulate the expression of ZmRD17, ZmAFP3, ZmPP2C, and ZmARR16 under drought. Our findings provide a detailed overview of the molecular mechanism controlling ZmCCT functions and highlight that ZmCCT has multiple roles in promoting abiotic stress tolerance.

Quantivine: A Visualization Approach for Large-Scale Quantum Circuit Representation and Analysis.

Quantum computing is a rapidly evolving field that enables exponential speed-up over classical algorithms. At the heart of this revolutionary technology are quantum circuits, which serve as vital tools for implementing, analyzing, and optimizing quantum algorithms. Recent advancements in quantum computing and the increasing capability of quantum devices have led to the development of more complex quantum circuits. However, traditional quantum circuit diagrams suffer from scalability and readability issues, which limit the efficiency of analysis and optimization processes. In this research, we propose a novel visualization approach for large-scale quantum circuits by adopting semantic analysis to facilitate the comprehension of quantum circuits. We first exploit meta-data and semantic information extracted from the underlying code of quantum circuits to create component segmentations and pattern abstractions, allowing for easier wrangling of massive circuit diagrams. We then develop Quantivine, an interactive system for exploring and understanding quantum circuits. A series of novel circuit visualizations is designed to uncover contextual details such as qubit provenance, parallelism, and entanglement. The effectiveness of Quantivine is demonstrated through two usage scenarios of quantum circuits with up to 100 qubits and a formal user evaluation with quantum experts. A free copy of this paper and all supplemental materials are available at https://osf.io/2m9yh/?view_only=0aa1618c97244f5093cd7ce15f1431f9.

Action-Evaluator: A Visualization Approach for Player Action Evaluation in Soccer.

In soccer, player action evaluation provides a fine-grained method to analyze player performance and plays an important role in improving winning chances in future matches. However, previous studies on action evaluation only provide a score for each action, and hardly support inspecting and comparing player actions integrated with complex match context information such as team tactics and player locations. In this work, we collaborate with soccer analysts and coaches to characterize the domain problems of evaluating player performance based on action scores. We design a tailored visualization of soccer player actions that places the action choice together with the tactic it belongs to as well as the player locations in the same view. Based on the design, we introduce a visual analytics system, Action-Evaluator, to facilitate a comprehensive player action evaluation through player navigation, action investigation, and action explanation. With the system, analysts can find players to be analyzed efficiently, learn how they performed under various match situations, and obtain valuable insights to improve their action choices. The usefulness and effectiveness of this work are demonstrated by two case studies on a real-world dataset and an expert interview.