Collaborative Noisy Label Cleaner: Learning Scene-aware Trailers for Multi-modal Highlight Detection in Movies

Movie highlights stand out of the screenplay for efficient browsing and play a crucial role on social media platforms. Based on existing efforts, this work has two observations: (1) For different annotators, labeling highlight has uncertainty, which leads to inaccurate and time-consuming annotations. (2) Besides previous supervised or unsupervised settings, some existing video corpora can be useful, e.g., trailers, but they are often noisy and incomplete to cover the full highlights. In this work, we study a more practical and promising setting, i.e., reformulating highlight detection as "learning with noisy labels". This setting does not require time-consuming manual annotations and can fully utilize existing abundant video corpora. First, based on movie trailers, we leverage scene segmentation to obtain complete shots, which are regarded as noisy labels. Then, we propose a Collaborative noisy Label Cleaner (CLC) framework to learn from noisy highlight moments. CLC consists of two modules: augmented cross-propagation (ACP) and multi-modality cleaning (MMC). The former aims to exploit the closely related audio-visual signals and fuse them to learn unified multi-modal representations. The latter aims to achieve cleaner highlight labels by observing the changes in losses among different modalities. To verify the effectiveness of CLC, we further collect a large-scale highlight dataset named MovieLights. Comprehensive experiments on MovieLights and YouTube Highlights datasets demonstrate the effectiveness of our approach. Code has been made available at: https://github.com/TencentYoutuResearch/HighlightDetection-CLCComment: Accepted to CVPR202

D3G: Exploring Gaussian Prior for Temporal Sentence Grounding with Glance Annotation

Temporal sentence grounding (TSG) aims to locate a specific moment from an untrimmed video with a given natural language query. Recently, weakly supervised methods still have a large performance gap compared to fully supervised ones, while the latter requires laborious timestamp annotations. In this study, we aim to reduce the annotation cost yet keep competitive performance for TSG task compared to fully supervised ones. To achieve this goal, we investigate a recently proposed glance-supervised temporal sentence grounding task, which requires only single frame annotation (referred to as glance annotation) for each query. Under this setup, we propose a Dynamic Gaussian prior based Grounding framework with Glance annotation (D3G), which consists of a Semantic Alignment Group Contrastive Learning module (SA-GCL) and a Dynamic Gaussian prior Adjustment module (DGA). Specifically, SA-GCL samples reliable positive moments from a 2D temporal map via jointly leveraging Gaussian prior and semantic consistency, which contributes to aligning the positive sentence-moment pairs in the joint embedding space. Moreover, to alleviate the annotation bias resulting from glance annotation and model complex queries consisting of multiple events, we propose the DGA module, which adjusts the distribution dynamically to approximate the ground truth of target moments. Extensive experiments on three challenging benchmarks verify the effectiveness of the proposed D3G. It outperforms the state-of-the-art weakly supervised methods by a large margin and narrows the performance gap compared to fully supervised methods. Code is available at https://github.com/solicucu/D3G.Comment: ICCV202

Unified and Dynamic Graph for Temporal Character Grouping in Long Videos

Video temporal character grouping locates appearing moments of major characters within a video according to their identities. To this end, recent works have evolved from unsupervised clustering to graph-based supervised clustering. However, graph methods are built upon the premise of fixed affinity graphs, bringing many inexact connections. Besides, they extract multi-modal features with kinds of models, which are unfriendly to deployment. In this paper, we present a unified and dynamic graph (UniDG) framework for temporal character grouping. This is accomplished firstly by a unified representation network that learns representations of multiple modalities within the same space and still preserves the modality's uniqueness simultaneously. Secondly, we present a dynamic graph clustering where the neighbors of different quantities are dynamically constructed for each node via a cyclic matching strategy, leading to a more reliable affinity graph. Thirdly, a progressive association method is introduced to exploit spatial and temporal contexts among different modalities, allowing multi-modal clustering results to be well fused. As current datasets only provide pre-extracted features, we evaluate our UniDG method on a collected dataset named MTCG, which contains each character's appearing clips of face and body and speaking voice tracks. We also evaluate our key components on existing clustering and retrieval datasets to verify the generalization ability. Experimental results manifest that our method can achieve promising results and outperform several state-of-the-art approaches

Can oblique lateral interbody fusion (OLIF) create more lumbosacral lordosis in lumbar spine surgery than minimally invasive transforaminal interbody fusion (MIS-TLIF)?

ObjectiveTo compare the differences in the correction effect for lumbosacral lordosis and clinical outcomes between OLIF with/without posterior pedicle screw fixation (PSF) and MIS-TLIF through a retrospective cohort study.MethodThere were 98 consecutive patients originally enrolled for the study, but 15 patients were excluded due to intraoperative endplate injury or osteotomy performed for severe spinal deformity. Thus, 83 patients included in this study (36 males and 47 females, mean age 65.8 years) underwent single to three-segment OLIF (including OLIF + PSF and OLIF Standalone) or MIS-TLIF surgery from 2016 to 2018. The operation time, bleeding and blood transfusion, fusion rate, complication, pre-and postoperative visual analogue scale (VAS), Oswestry Disability Index (ODI) were evaluated. In addition, radiological parameters including lumbosacral lordosis (LL), fused segment lordosis (FSL), anterior disc height (ADH) and posterior disc height (PDH) were measured. The clinical outcomes, LL, FSL, ADH and PDH restored and were compared between the OLIF group, OLIF subgroups and MIS-TLIF group.ResultsThe average operation time and intraoperative bleeding were significantly less in the OLIF group than in the MIS-TLIF group (163 ± 68 vs. 233 ± 79 min, 116 ± 148 vs. 434 ± 201 ml, P < 0.001). There was no statistically significant difference between the OLIF group and the MIS-TLIF group in VAS and ODI improvements, fusion rate, complication, LL and FSL correction (P > 0.05). The ADH and PDH increases in the OLIF group were more than that in MIS-TLIF group (P < 0.001). The correction of LL was significantly more in the OLIF + PSF group than in the MIS-TLIF group (9.9 ± 11.1 vs. 4.2 ± 6.1deg, P = 0.034).ConclusionOLIF and MIS-TLIF are both safe and effective procedures, capable of restoring lumbosacral lordosis and disc height partly. Combined with PSF, OLIF can achieve a better correction effect of lumbosacral lordosis than MIS-TLIF

Selection of Pru p 3 hypoallergenic peach and nectarine varieties

To the Editor, Peach is an important fruit consumed worldwide. However, it is also one of the most frequently reported allergenic fruits.1 Component diagnosis of peach allergy indicates Pru p 1, Pru p 2, Pru p 3, Pru p 4, Pru p 7, and Pru p 9 are involved.2, 3 Pru p 3 is the dominant allergen responsible for severe allergic reaction,4 and it is considered to be the primary sensitizer to other LTPs in Mediterranean and Central Europe.5 The levels of Pru p 3 differ between varieties.6 To date, measurement of Pru p 3 in a limited number of peach and nectarines from Spain, United States, and Italy has been reported.7 Significant variation of allergen concentration in processed foods containing peach has also been observed.8 The content of Pru p 3 of peach/nectarine determines the potential risk for peach allergic patients. China is the origin of peach with representative genetic diversity to be explored for hypoallergenic varieties.9 A core collection of 103 varieties cultivated in Jiaxing, Zhejiang Province were selected to represent this diversity, including 23 nectarines and 80 peach varieties (with fruit hair, round or flat, 77 cultivated, three wild) (Table S1). The soluble solid content (SSC), ripening date, and peach aroma intensity were recorded. Specific methods are detailed in the Supporting Information. Pru p 3 was quantified by ELISA based on our previous research.6info:eu-repo/semantics/publishedVersio

Crystal structure of Pyrococcus horikoshii tryptophanyl-tRNA synthetase and structure-based phylogenetic analysis suggest an archaeal origin of tryptophanyl-tRNA synthetase

The ancient and ubiquitous aminoacyl-tRNA synthetases constitute a valuable model system for studying early evolutionary events. So far, the evolutionary relationship of tryptophanyl- and tyrosyl-tRNA synthetase (TrpRS and TyrRS) remains controversial. As TrpRS and TyrRS share low sequence homology but high structural similarity, a structure-based method would be advantageous for phylogenetic analysis of the enzymes. Here, we present the first crystal structure of an archaeal TrpRS, the structure of Pyrococcus horikoshii TrpRS (pTrpRS) in complex with tryptophanyl-5′ AMP (TrpAMP) at 3.0 Å resolution which demonstrates more similarities to its eukaryotic counterparts. With the pTrpRS structure, we perform a more complete structure-based phylogenetic study of TrpRS and TyrRS, which for the first time includes representatives from all three domains of life. Individually, each enzyme shows a similar evolutionary profile as observed in the sequence-based phylogenetic studies. However, TyrRSs from Archaea/Eucarya cluster with TrpRSs rather than their bacterial counterparts, and the root of TrpRS locates in the archaeal branch of TyrRS, indicating the archaeal origin of TrpRS. Moreover, the short distance between TrpRS and archaeal TyrRS and that between bacterial and archaeal TrpRS, together with the wide distribution of TrpRS, suggest that the emergence of TrpRS and subsequent acquisition by Bacteria occurred at early stages of evolution

De novo DHDDS variants cause a neurodevelopmental and neurodegenerative disorder with myoclonus

Subcellular membrane systems are highly enriched in dolichol, whose role in organelle homeostasis and endosomal-lysosomal pathway remains largely unclear besides being involved in protein glycosylation. DHDDS encodes for the catalytic subunit (DHDDS) of the enzyme cis-prenyltransferase (cis-PTase), involved in dolichol biosynthesis and dolichol-dependent protein glycosylation in the endoplasmic reticulum. An autosomal recessive form of retinitis pigmentosa (retinitis pigmentosa 59) has been associated with a recurrent DHDDS variant. Moreover, two recurring de novo substitutions were detected in a few cases presenting with neurodevelopmental disorder, epilepsy, and movement disorder. We evaluated a large cohort of patients (n=25) with de novo pathogenic variants in DHDDS and provided the first systematic description of the clinical features and long-term outcome of this new neurodevelopmental and neurodegenerative disorder. The functional impact of the identified variants was explored by yeast complementation system and enzymatic assay. Patients presented during infancy or childhood with a variable association of neurodevelopmental disorder, generalized epilepsy, action myoclonus/cortical tremor, and ataxia. Later in the disease course they experienced a slow neurological decline with the emergence of hyperkinetic and/or hypokinetic movement disorder, cognitive deterioration, and psychiatric disturbances. Storage of lipidic material and altered lysosomes were detected in myelinated fibers and fibroblasts, suggesting a dysfunction of the lysosomal enzymatic scavenger machinery. Serum glycoprotein hypoglycosylation was not detected and, in contrast to retinitis pigmentosa and other congenital disorders of glycosylation involving dolichol metabolism, the urinary dolichol D18/D19 ratio was normal. Mapping the disease-causing variants into the protein structure revealed that most of them clustered around the active site of the DHDDS subunit. Functional studies using yeast complementation assay and in vitro activity measurements confirmed that these changes affected the catalytic activity of the cis-PTase and showed growth defect in yeast complementation system as compared with the wild-type enzyme and retinitis pigmentosa-associated protein. In conclusion, we characterized a distinctive neurodegenerative disorder due to de novo DHDDS variants, which clinically belongs to the spectrum of genetic progressive encephalopathies with myoclonus. Clinical and biochemical data from this cohort depicted a condition at the intersection of congenital disorders of glycosylation and inherited storage diseases with several features akin to of progressive myoclonus epilepsy such as neuronal ceroid lipofuscinosis and other lysosomal disorders

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO