Data-driven Loop Closure Detection in Bathymetric Point Clouds for Underwater SLAM

Simultaneous localization and mapping (SLAM) frameworks for autonomous navigation rely on robust data association to identify loop closures for back-end trajectory optimization. In the case of autonomous underwater vehicles (AUVs) equipped with multibeam echosounders (MBES), data association is particularly challenging due to the scarcity of identifiable landmarks in the seabed, the large drift in dead-reckoning navigation estimates to which AUVs are prone and the low resolution characteristic of MBES data. Deep learning solutions to loop closure detection have shown excellent performance on data from more structured environments. However, their transfer to the seabed domain is not immediate and efforts to port them are hindered by the lack of bathymetric datasets. Thus, in this paper we propose a neural network architecture aimed to showcase the potential of adapting such techniques to correspondence matching in bathymetric data. We train our framework on real bathymetry from an AUV mission and evaluate its performance on the tasks of loop closure detection and coarse point cloud alignment. Finally, we show its potential against a more traditional method and release both its implementation and the dataset used

Component attention network for multimodal dance improvisation recognition

Dance improvisation is an active research topic in the arts. Motion analysis of improvised dance can be challenging due to its unique dynamics. Data-driven dance motion analysis, including recognition and generation, is often limited to skeletal data. However, data of other modalities, such as audio, can be recorded and benefit downstream tasks. This paper explores the application and performance of multimodal fusion methods for human motion recognition in the context of dance improvisation. We propose an attention-based model, component attention network (CANet), for multimodal fusion on three levels: 1) feature fusion with CANet, 2) model fusion with CANet and graph convolutional network (GCN), and 3) late fusion with a voting strategy. We conduct thorough experiments to analyze the impact of each modality in different fusion methods and distinguish critical temporal or component features. We show that our proposed model outperforms the two baseline methods, demonstrating its potential for analyzing improvisation in dance.Comment: Accepted to 25th ACM International Conference on Multimodal Interaction (ICMI 2023

CUCHILD: A Large-Scale Cantonese Corpus of Child Speech for Phonology and Articulation Assessment

This paper describes the design and development of CUCHILD, a large-scale Cantonese corpus of child speech. The corpus contains spoken words collected from 1,986 child speakers aged from 3 to 6 years old. The speech materials include 130 words of 1 to 4 syllables in length. The speakers cover both typically developing (TD) children and children with speech disorder. The intended use of the corpus is to support scientific and clinical research, as well as technology development related to child speech assessment. The design of the corpus, including selection of words, participants recruitment, data acquisition process, and data pre-processing are described in detail. The results of acoustical analysis are presented to illustrate the properties of child speech. Potential applications of the corpus in automatic speech recognition, phonological error detection and speaker diarization are also discussed.Comment: Accepted to INTERSPEECH 2020, Shanghai, Chin

Yeast Golden Gate: Standardized Assembly of S. cerevisiae Transcriptional Units

BBF RFC 88 describes a new standard for the assembly of basic Saccharomyces cerevisiae transcriptional units (TUs) consisting of a promoter/5’untranslated region (UTR), open reading frame (ORF), and 3’UTR/terminator. Note that we use the term “promoter” here to refer to both the promoter and the 5’ UTR, which we currently define as a single part. Future iterations of this standard will incorporate subdivision of currently defined parts e.g. into promoter and 5’ UTR. The standard makes use of the type IIS restriction enzyme BsaI to generate standardized and user­‐defined ‘signature overhangs’, thus enabling directional and seamless TU assembly. RFC88 is supported by the Yeast Standardized Collection of Parts for Expression (SCoPE), a repository of subcloned and sequence verified parts compatible with this assembly standard. The Yeast SCoPE is currently populated by a large number of S. cerevisiae promoters and terminators that facilitate expression and characterization of non­‐native ORFs

Traffic-Aware Multi-Camera Tracking of Vehicles Based on ReID and Camera Link Model

Multi-target multi-camera tracking (MTMCT), i.e., tracking multiple targets across multiple cameras, is a crucial technique for smart city applications. In this paper, we propose an effective and reliable MTMCT framework for vehicles, which consists of a traffic-aware single camera tracking (TSCT) algorithm, a trajectory-based camera link model (CLM) for vehicle re-identification (ReID), and a hierarchical clustering algorithm to obtain the cross camera vehicle trajectories. First, the TSCT, which jointly considers vehicle appearance, geometric features, and some common traffic scenarios, is proposed to track the vehicles in each camera separately. Second, the trajectory-based CLM is adopted to facilitate the relationship between each pair of adjacently connected cameras and add spatio-temporal constraints for the subsequent vehicle ReID with temporal attention. Third, the hierarchical clustering algorithm is used to merge the vehicle trajectories among all the cameras to obtain the final MTMCT results. Our proposed MTMCT is evaluated on the CityFlow dataset and achieves a new state-of-the-art performance with IDF1 of 74.93%.Comment: Accepted by ACM International Conference on Multimedia 202

A possible pathway for rapid growth of sulfate during haze days in China

Rapid industrialization and urbanization have caused frequent occurrence of haze in China during wintertime in recent years. The sulfate aerosol is one of the most important components of fine particles (PM[subscript 2. 5]) in the atmosphere, contributing significantly to the haze formation. However, the heterogeneous formation mechanism of sulfate remains poorly characterized. The relationships of the observed sulfate with PM[subscript 2. 5], iron, and relative humidity in Xi'an, China have been employed to evaluate the mechanism and to develop a parameterization of the sulfate heterogeneous formation involving aerosol water for incorporation into atmospheric chemical transport models. Model simulations with the proposed parameterization can successfully reproduce the observed sulfate rapid growth and diurnal variations in Xi'an and Beijing, China. Reasonable representation of sulfate heterogeneous formation in chemical transport models considerably improves the PM2. 5 simulations, providing the underlying basis for better understanding the haze formation and supporting the design and implementation of emission control strategies

Investigation on the Efficiency of Chinese Herbal Injections combined with Concurrent Chemoradiotherapy for Treating Nasopharyngeal Carcinoma based on Multidimensional Bayesian Network Meta-analysis

Introduction: Given the wide utilization of Chinese herbal injections in the treatment of nasopharyngeal carcinoma (NPC), this network meta-analysis (NMA) was devised to compare the clinical efficacy and safety of different Chinese herbal injections combined with concurrent chemoradiotherapy (CCRT) against NPC.Methods: Randomized controlled trials (RCTs) were retrieved from seven electronic databases from the date of database establishment to October 5, 2020. Study selection and data extraction conformed to a priori criteria. Focusing on clinical effective rate, performance status, grade ≥3 oral mucositis, nausea and vomiting, leukopenia, and thrombopenia, this NMA was performed with Review Manager 5.3.5, Stata 13.1, WinBUGS 1.4.3, and R 4.0.3 software.Results: Ten inventions from 37 RCTs involving 2,581 participants with NPC that evaluated the clinical effective rate, nausea and vomiting, leukopenia, thrombopenia, and grade ≥3 oral mucositis were included. Compared with CCRT alone, Elemene injection and Compound Kushen injection were associated with significantly improved clinical effective rates, and Elemene injection plus CCRT had the highest probability in terms of clinical effective rate (78.07%) compared with the other interventions. Shenqifuzheng injection, Xiaoaiping injection, and Shenmai injection ranked the best in terms of performance status (79.02%), nausea and vomiting (86.35%), and grade ≥3 oral mucositis (78.14%) when combined with CCRT. Kangai injection combined with CCRT ranked ahead of the other injections in terms of leukopenia (90.80%) and thrombopenia (91.04%), and had a better impact on improving performance status and reducing leukopenia, thrombopenia, grade ≥3 oral mucositis, and nausea and vomiting in the multidimensional cluster analysis.Conclusion: Current clinical evidence indicates that Elemene injection combined with CCRT has the best clinical effective rate and that Kangai injection might have a comprehensively better impact on improving performance status and reducing adverse reactions against NPC. Additionally, due to the limitations of this NMA, more multicenter, high-quality, and head-to-head RCTs are needed to properly support our findings

Local Diffusion Homogeneity Provides Supplementary Information in T2DM-Related WM Microstructural Abnormality Detection

Objectives: We aimed to investigate whether an inter-voxel diffusivity metric (local diffusion homogeneity, LDH), can provide supplementary information to traditional intra-voxel metrics (i.e., fractional anisotropy, FA) in white matter (WM) abnormality detection for type 2 diabetes mellitus (T2DM).Methods: Diffusion tensor imaging was acquired from 34 T2DM patients and 32 healthy controls. Voxel-based group-difference comparisons based on LDH and FA, as well as the association between the diffusion metrics and T2DM risk factors [i.e., body mass index (BMI) and systolic blood pressure (SBP)], were conducted, with age, gender and education level controlled.Results: Compared to the controls, T2DM patients had higher LDH in the pons and left temporal pole, as well as lower FA in the left superior corona radiation (p < 0.05, corrected). In T2DM, there were several overlapping WM areas associated with BMI as revealed by both LDH and FA, including right temporal lobe and left inferior parietal lobe; but the unique areas revealed only by using LDH included left inferior temporal lobe, right supramarginal gyrus, left pre- and post-central gyrus (at the semiovale center), and right superior radiation. Overlapping WM areas that associated with SBP were found with both LDH and FA, including right temporal pole, bilateral orbitofrontal area (rectus gyrus), the media cingulum bundle, and the right cerebellum crus I. However, the unique areas revealed only by LDH included right inferior temporal lobe, right inferior occipital lobe, and splenium of corpus callosum.Conclusion: Inter- and intra-voxel diffusivity metrics may have different sensitivity in the detection of T2DM-related WM abnormality. We suggested that LDH could provide supplementary information and reveal additional underlying brain changes due to diabetes

Corrigendum: Revealing the mechanism of Huazhi Rougan granule in the treatment of nonalcoholic fatty liver through intestinal flora based on 16S rRNA, metagenomic sequencing and network pharmacology

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Synchronous post-acceleration of laser-driven protons in helical coil targets by controlling the current dispersion

Post-acceleration of protons in helical coil targets driven by intense, ultrashort laser pulses can enhance ion energy by utilizing the transient current from the targets’ self-discharge. The acceleration length of protons can exceed a few millimeters, and the acceleration gradient is of the order of GeV/m. How to ensure the synchronization between the accelerating electric field and the protons is a crucial problem for efficient post-acceleration. In this paper, we study how the electric field mismatch induced by current dispersion affects the synchronous acceleration of protons. We propose a scheme using a two-stage helical coil to control the current dispersion. With optimized parameters, the energy gain of protons is increased by four times. Proton energy is expected to reach 45 MeV using a hundreds-of-terawatts laser, or more than 100 MeV using a petawatt laser, by controlling the current dispersion