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High-redshift radio(-loud) galaxies (H$z$RGs) are massive galaxies with powerful radio-loud active galactic nuclei (AGNs) and serve as beacons for protocluster identification. However, the interplay between H$z$RGs and the large-scale environment remains unclear. To understand the connection between H$z$RGs and the surrounding obscured star formation, we investigated the overdensity and spatial distribution of submillimeter-bright galaxies (SMGs) in the field of 4C\,23.56, a well-known H$z$RG at $z=2.48$. We used SCUBA-2 data ($\sigma\,{\sim}\,0.6$\,mJy) to estimate the $850\,{\rm \mu m}$ source number counts and examine the radial and azimuthal overdensities of the $850\,{\rm \mu m}$ sources in the vicinity of the H$z$RG. The angular distribution of SMGs is inhomogeneous around the H$z$RG 4C\,23.56, with fewer sources oriented along the radio jet. We also find a significant overdensity of bright SMGs (${\rm S}_{850\rm\,\mu m}\geq5\,$mJy). Faint and bright SMGs exhibit different spatial distributions. The former are concentrated in the core region, while the latter prefer the outskirts of the H$z$RG field. High-resolution observations show that the seven brightest SMGs in our sample are intrinsically bright, suggesting that the overdensity of bright SMGs is less likely due to the source multiplicity.

High-redshift radio(-loud) galaxies (H$z$RGs) are massive galaxies with powerful radio-loud active galactic nuclei (AGNs) and serve as beacons for protocluster identification. However, the interplay between H$z$RGs and the large-scale environment remains unclear. To understand the connection between H$z$RGs and the surrounding obscured star formation, we investigated the overdensity and spatial distribution of submillimeter-bright galaxies (SMGs) in the field of 4C\,23.56, a well-known H$z$RG at $z=2.48$. We used SCUBA-2 data ($\sigma\,{\sim}\,0.6$\,mJy) to estimate the $850\,{\rm \mu m}$ source number counts and examine the radial and azimuthal overdensities of the $850\,{\rm \mu m}$ sources in the vicinity of the H$z$RG. The angular distribution of SMGs is inhomogeneous around the H$z$RG 4C\,23.56, with fewer sources oriented along the radio jet. We also find a significant overdensity of bright SMGs (${\rm S}_{850\rm\,\mu m}\geq5\,$mJy). Faint and bright SMGs exhibit different spatial distributions. The former are concentrated in the core region, while the latter prefer the outskirts of the H$z$RG field. High-resolution observations show that the seven brightest SMGs in our sample are intrinsically bright, suggesting that the overdensity of bright SMGs is less likely due to the source multiplicity.

Xia Li,1 Yue Jin,1 Jian Xue2 1Department of Molecular Diagnosis, Northern Jiangsu People’s Hospital, Yangzhou, People’s Republic of China; 2Department of Emergency Medicine, Yizheng People’s Hospital, Yangzhou, People’s Republic of ChinaCorrespondence: Yue Jin, Department of Molecular Diagnosis, Northern Jiangsu People’s Hospital, No. 98, Nantong West Road, Yangzhou, Jiangsu Province, People’s Republic of China, Email yyue_king@163.comAbstract: Collagen, the predominant protein constituent of the mammalian extracellular matrix (ECM), comprises a diverse family of 28 members (I–XXVIII). Beyond its structural significance, collagen is implicated in various diseases or cancers, notably breast cancer, where it influences crucial cellular processes including proliferation, metastasis, apoptosis, and drug resistance, intricately shaping cancer progression and prognosis. In breast cancer, distinct collagens exhibit differential expression profiles, with some showing heightened or diminished levels in cancerous tissues or cells compared to normal counterparts, suggesting specific and pivotal biological functions. In this review, we meticulously analyze the expression of individual collagen members in breast cancer, utilizing Transcripts Per Million (TPM) data sourced from the GEPIA2 database. Through this analysis, we identify collagens that deviate from normal expression patterns in breast cancer, providing a comprehensive overview of their expression dynamics, functional roles, and underlying mechanisms. Our findings shed light on recent advancements in understanding the intricate interplay between these aberrantly expressed collagens and breast cancer. This exploration aims to offer valuable insights for the identification of potential biomarkers and therapeutic targets, thereby advancing the prospects of more effective interventions in breast cancer treatment.Keywords: collagen, breast cancer, extracellular matrix, prognostic marker

In this work, we investigate the spectroscopy of higher $B_c$ mesons, with a special focus on the consideration of the unquenched effects. To account for such effects, we employ the modified Godfrey-Isgur model and introduce a screening potential. The resulting mass spectrum of the concerned higher $B_c$ states is then presented, showing significant deviations after considering the unquenched effects. This emphasizes the importance of considering the unquenched effects when studying of the higher $B_c$ mesons. Furthermore, we determine the corresponding spatial wave functions of these $B_c$ mesons, which have practical applications in subsequent studies of their decays. These decays include two-body Okuba-Zweig-Iizuka allowed strong decays, dipion transitions between $B_c$ mesons, radiative decays, and some typical weak decays. With the ongoing high-luminosity upgrade of the Large Hadron Collider, we expect the discovery of additional $B_c$ states in the near future. The knowledge gained from the mass spectrum and the different decay modes will undoubtedly provide valuable insights for future experimental explorations of these higher $B_c$ mesons., Comment: 30 pages, 7 figures and 17 tables

AbstractMixed ionic‐electronic conducting (MIEC) membranes have gained growing interest recently for various promising environmental and energy applications, such as H2 and O2 production, CO2 reduction, O2 and H2 separation, CO2 separation, membrane reactors for production of chemicals, cathode development for solid oxide fuel cells, solar‐driven evaporation and energy‐saving regeneration as well as electrolyzer cells for power‐to‐X technologies. The purpose of this roadmap, written by international specialists in their fields, is to present a snapshot of the state‐of‐the‐art, and provide opinions on the future challenges and opportunities in this complex multidisciplinary research field. As the fundamentals of using MIEC membranes for various applications become increasingly challenging tasks, particularly in view of the growing interdisciplinary nature of this field, a better understanding of the underlying physical and chemical processes is also crucial to enable the career advancement of the next generation of researchers. As an integrated and combined article, it is hoped that this roadmap, covering all these aspects, will be informative to support further progress in academics as well as in the industry‐oriented research toward commercialization of MIEC membranes for different applications.

In this work, we investigate the spectroscopy of higher $B_c$ mesons, with a special focus on the consideration of the unquenched effects. To account for such effects, we employ the modified Godfrey-Isgur model and introduce a screening potential. The resulting mass spectrum of the concerned higher $B_c$ states is then presented, showing significant deviations after considering the unquenched effects. This emphasizes the importance of considering the unquenched effects when studying of the higher $B_c$ mesons. Furthermore, we determine the corresponding spatial wave functions of these $B_c$ mesons, which have practical applications in subsequent studies of their decays. These decays include two-body Okuba-Zweig-Iizuka allowed strong decays, dipion transitions between $B_c$ mesons, radiative decays, and some typical weak decays. With the ongoing high-luminosity upgrade of the Large Hadron Collider, we expect the discovery of additional $B_c$ states in the near future. The knowledge gained from the mass spectrum and the different decay modes will undoubtedly provide valuable insights for future experimental explorations of these higher $B_c$ mesons., Comment: 30 pages, 7 figures and 17 tables

In this paper, the Thaumantis diores Doubleday, 1845-complex, including T. diores Doubleday, 1845 and T.hainana (Crowley, 1900), is studied, and a new subspecies, T. hainana libodiores Lang & Wang, ssp. nov., is described from Guizhou province, S.W. China, En este trabajo se estudia el complejo Thaumantis diores Doubleday, 1845, que incluye T. diores Doubleday,1845 y T. hainana (Crowley, 1900) y se describe una nueva subespecie, T. hainana libodiores Lang & Wang, ssp.nov., de la provincia de Guizhou, suroeste de China.

In this work, we investigate the spectroscopy of higher $B_c$ mesons, with a special focus on the consideration of the unquenched effects. To account for such effects, we employ the modified Godfrey-Isgur model and introduce a screening potential. The resulting mass spectrum of the concerned higher $B_c$ states is then presented, showing significant deviations after considering the unquenched effects. This emphasizes the importance of considering the unquenched effects when studying of the higher $B_c$ mesons. Furthermore, we determine the corresponding spatial wave functions of these $B_c$ mesons, which have practical applications in subsequent studies of their decays. These decays include two-body Okuba-Zweig-Iizuka allowed strong decays, dipion transitions between $B_c$ mesons, radiative decays, and some typical weak decays. With the ongoing high-luminosity upgrade of the Large Hadron Collider, we expect the discovery of additional $B_c$ states in the near future. The knowledge gained from the mass spectrum and the different decay modes will undoubtedly provide valuable insights for future experimental explorations of these higher $B_c$ mesons., Comment: 30 pages, 7 figures and 17 tables

We propose gated language experts and curriculum training to enhance multilingual transformer transducer models without requiring language identification (LID) input from users during inference. Our method incorporates a gating mechanism and LID loss, enabling transformer experts to learn language-specific information. By combining gated transformer experts with shared transformer layers, we construct multilingual transformer blocks and utilize linear experts to effectively regularize the joint network. The curriculum training scheme leverages LID to guide the gated experts in improving their respective language performance. Experimental results on a bilingual task involving English and Spanish demonstrate significant improvements, with average relative word error reductions of 12.5% and 7.3% compared to the baseline bilingual and monolingual models, respectively. Notably, our method achieves performance comparable to the upper-bound model trained and inferred with oracle LID. Extending our approach to trilingual, quadrilingual, and pentalingual models reveals similar advantages to those observed in the bilingual models, highlighting its ease of extension to multiple languages.

Astrochemistry has been widely developed as a power tool to probe physical properties of the interstellar medium (ISM) in various conditions of the Milky Way (MW) Galaxy, and in near and distant galaxies. Most current studies conventionally apply linear scaling to all elemental abundances based on the gas-phase metallicity. However, these elements, including carbon and oxygen, are enriched differentially by stellar nucleosynthesis and the overall galactic chemical evolution, evident from $\alpha$-enhancement in multiple galactic observations such as starbursts, high-redshift star-forming galaxies, and low-metallicity dwarfs. We perform astrochemical modeling to simulate the impact of an $\alpha$-enhanced ISM gas cloud on the abundances of the three phases of carbon (C$^+$, C, CO) dubbed as `the carbon cycle'. The ISM environmental parameters considered include two cosmic-ray ionization rates ($\zeta_{\rm CR}=10^{-17}$ and $10^{-15}\,{\rm s}^{-1}$), two isotropic FUV radiation field strengths ($\chi/\chi_0=1$ and $10^2$), and (sub-)linear dust-to-gas relations against metallicity, mimicking the ISM conditions of different galaxy types. In galaxies with [C/O] $<$ 0, CO, C and C$^+$ all decrease in both abundances and emission, though with differential biases. The low-$J$ CO emission is found to be the most stable tracer for the molecular gas, while C and C$^+$ trace H$_2$ gas only under limited conditions, in line with recent discoveries of [CI]-dark galaxies. We call for caution when using [CII]~$158\mu$m and [CI](1-0) as alternative H$_2$-gas tracers for both diffuse and dense gas with non-zero [C/O] ratios., Comment: MNRAS accepted. 21 pages, 15 figures, comments welcome!

The growing need for instant spoken language transcription and translation is driven by increased global communication and cross-lingual interactions. This has made offering translations in multiple languages essential for user applications. Traditional approaches to automatic speech recognition (ASR) and speech translation (ST) have often relied on separate systems, leading to inefficiencies in computational resources, and increased synchronization complexity in real time. In this paper, we propose a streaming Transformer-Transducer (T-T) model able to jointly produce many-to-one and one-to-many transcription and translation using a single decoder. We introduce a novel method for joint token-level serialized output training based on timestamp information to effectively produce ASR and ST outputs in the streaming setting. Experiments on {it,es,de}->en prove the effectiveness of our approach, enabling the generation of one-to-many joint outputs with a single decoder for the first time., Comment: \c{opyright} 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Simultaneous Speech-to-Text translation serves a critical role in real-time crosslingual communication. Despite the advancements in recent years, challenges remain in achieving stability in the translation process, a concern primarily manifested in the flickering of partial results. In this paper, we propose a novel revision-controllable method designed to address this issue. Our method introduces an allowed revision window within the beam search pruning process to screen out candidate translations likely to cause extensive revisions, leading to a substantial reduction in flickering and, crucially, providing the capability to completely eliminate flickering. The experiments demonstrate the proposed method can significantly improve the decoding stability without compromising substantially on the translation quality., Comment: accepted by ASRU 2023

End-to-end speech translation (ST) for conversation recordings involves several under-explored challenges such as speaker diarization (SD) without accurate word time stamps and handling of overlapping speech in a streaming fashion. In this work, we propose DiariST, the first streaming ST and SD solution. It is built upon a neural transducer-based streaming ST system and integrates token-level serialized output training and t-vector, which were originally developed for multi-talker speech recognition. Due to the absence of evaluation benchmarks in this area, we develop a new evaluation dataset, DiariST-AliMeeting, by translating the reference Chinese transcriptions of the AliMeeting corpus into English. We also propose new metrics, called speaker-agnostic BLEU and speaker-attributed BLEU, to measure the ST quality while taking SD accuracy into account. Our system achieves a strong ST and SD capability compared to offline systems based on Whisper, while performing streaming inference for overlapping speech. To facilitate the research in this new direction, we release the evaluation data, the offline baseline systems, and the evaluation code., Comment: Accepted to ICASSP 2024

In this paper, we explore the zero-shot capability of the Segment Anything Model (SAM) for food image segmentation. To address the lack of class-specific information in SAM-generated masks, we propose a novel framework, called FoodSAM. This innovative approach integrates the coarse semantic mask with SAM-generated masks to enhance semantic segmentation quality. Besides, we recognize that the ingredients in food can be supposed as independent individuals, which motivated us to perform instance segmentation on food images. Furthermore, FoodSAM extends its zero-shot capability to encompass panoptic segmentation by incorporating an object detector, which renders FoodSAM to effectively capture non-food object information. Drawing inspiration from the recent success of promptable segmentation, we also extend FoodSAM to promptable segmentation, supporting various prompt variants. Consequently, FoodSAM emerges as an all-encompassing solution capable of segmenting food items at multiple levels of granularity. Remarkably, this pioneering framework stands as the first-ever work to achieve instance, panoptic, and promptable segmentation on food images. Extensive experiments demonstrate the feasibility and impressing performance of FoodSAM, validating SAM's potential as a prominent and influential tool within the domain of food image segmentation. We release our code at https://github.com/jamesjg/FoodSAM., Comment: Code is available at https://github.com/jamesjg/FoodSAM

In real-world applications, users often require both translations and transcriptions of speech to enhance their comprehension, particularly in streaming scenarios where incremental generation is necessary. This paper introduces a streaming Transformer-Transducer that jointly generates automatic speech recognition (ASR) and speech translation (ST) outputs using a single decoder. To produce ASR and ST content effectively with minimal latency, we propose a joint token-level serialized output training method that interleaves source and target words by leveraging an off-the-shelf textual aligner. Experiments in monolingual (it-en) and multilingual (\{de,es,it\}-en) settings demonstrate that our approach achieves the best quality-latency balance. With an average ASR latency of 1s and ST latency of 1.3s, our model shows no degradation or even improves output quality compared to separate ASR and ST models, yielding an average improvement of 1.1 WER and 0.4 BLEU in the multilingual case., Comment: Accepted at ASRU 2023

Mixed ionic‐electronic conducting (MIEC) membranes have gained growing interest recently for various promising environmental and energy applications, such as H₂ and O₂ production, CO₂ reduction, O₂ and H₂ separation, CO₂ separation, membrane reactors for production of chemicals, cathode development for solid oxide fuel cells, solar‐driven evaporation and energy‐saving regeneration as well as electrolyzer cells for power‐to‐X technologies. The purpose of this roadmap, written by international specialists in their fields, is to present a snapshot of the state‐of‐the‐art, and provide opinions on the future challenges and opportunities in this complex multidisciplinary research field. As the fundamentals of using MIEC membranes for various applications become increasingly challenging tasks, particularly in view of the growing interdisciplinary nature of this field, a better understanding of the underlying physical and chemical processes is also crucial to enable the career advancement of the next generation of researchers. As an integrated and combined article, it is hoped that this roadmap, covering all these aspects, will be informative to support further progress in academics as well as in the industry‐oriented research toward commercialization of MIEC membranes for different applications.

Mixed ionic‐electronic conducting (MIEC) membranes have gained growing interest recently for various promising environmental and energy applications, such as H₂ and O₂ production, CO₂ reduction, O₂ and H₂ separation, CO₂ separation, membrane reactors for production of chemicals, cathode development for solid oxide fuel cells, solar‐driven evaporation and energy‐saving regeneration as well as electrolyzer cells for power‐to‐X technologies. The purpose of this roadmap, written by international specialists in their fields, is to present a snapshot of the state‐of‐the‐art, and provide opinions on the future challenges and opportunities in this complex multidisciplinary research field. As the fundamentals of using MIEC membranes for various applications become increasingly challenging tasks, particularly in view of the growing interdisciplinary nature of this field, a better understanding of the underlying physical and chemical processes is also crucial to enable the career advancement of the next generation of researchers. As an integrated and combined article, it is hoped that this roadmap, covering all these aspects, will be informative to support further progress in academics as well as in the industry‐oriented research toward commercialization of MIEC membranes for different applications.

Qiao-Li Lan, Hao-Yue Sun, Yi Ye, Ying Wang, Ya Liu, Xue-Jian Weng Department of Digestive System, Wenzhou People’s Hospital, The Third Affiliated Hospital of Shanghai University, The Wenzhou Third Clinical College of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of ChinaCorrespondence: Ying Wang, Department of Digestive System, Wenzhou People’s Hospital, The Third Affiliated Hospital of Shanghai University, The Wenzhou Third Clinical College of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, People’s Republic of China, Tel +86 13758454419, Fax +86 057788059502, Email wangyingwytg@163.comObjective: This study aimed to investigate related factors affecting the eradication rate of Helicobacter pylori (Hp) by modified quadruple therapy.Methods: Between September 2020 and March 2021, 341 patients who were diagnosed with Hp infection and whose infections were confirmed by gastroscopy, a histological examination, and a C13-UBT without culturing and antimicrobial susceptibility studies received a two-week anti-Hp treatment, a modified quadruple therapy, in our department. The result of C13-UBT was rechecked 4 weeks after the drug withdrawal, and the patients were divided into two groups—a success group and a failure group—according to the final breath result. The general clinical information and related laboratory indexes of each patient were collected, and the factors affecting the eradication rate were analyzed.Results: The total clinical eradication rate was 80.06% (273/341), and the failure rate was 19.94% (68/341), correspondingly. Univariate analysis identified statistically significant differences between the two groups in serum 25-hydroxyvitamin D levels, presence of oral diseases, positive cytotoxin-associated gene A (CagA), and medical compliance (P < 0.05). Meanwhile, the use of a proton pump inhibitor (PPIs) and antibiotics was statistically different (P < 0.05). Logistic regression analysis revealed that vitamin D level

This paper proposes a novel application system for the generation of three-dimensional (3D) character animation driven by markerless human body motion capturing. The entire pipeline of the system consists of five stages: 1) the capturing of motion data using multiple cameras, 2) detection of the two-dimensional (2D) human body joints, 3) estimation of the 3D joints, 4) calculation of bone transformation matrices, and 5) generation of character animation. The main objective of this study is to generate a 3D skeleton and animation for 3D characters using multi-view images captured by ordinary cameras. The computational complexity of the 3D skeleton reconstruction based on 3D vision has been reduced as needed to achieve frame-by-frame motion capturing. The experimental results reveal that our system can effectively and efficiently capture human actions and use them to animate 3D cartoon characters in real-time.

Neural transducer is now the most popular end-to-end model for speech recognition, due to its naturally streaming ability. However, it is challenging to adapt it with text-only data. Factorized neural transducer (FNT) model was proposed to mitigate this problem. The improved adaptation ability of FNT on text-only adaptation data came at the cost of lowered accuracy compared to the standard neural transducer model. We propose several methods to improve the performance of the FNT model. They are: adding CTC criterion during training, adding KL divergence loss during adaptation, using a pre-trained language model to seed the vocabulary predictor, and an efficient adaptation approach by interpolating the vocabulary predictor with the n-gram language model. A combination of these approaches results in a relative word-error-rate reduction of 9.48\% from the standard FNT model. Furthermore, n-gram interpolation with the vocabulary predictor improves the adaptation speed hugely with satisfactory adaptation performance.

Automatic Speech Recognition (ASR) systems typically yield output in lexical form. However, humans prefer a written form output. To bridge this gap, ASR systems usually employ Inverse Text Normalization (ITN). In previous works, Weighted Finite State Transducers (WFST) have been employed to do ITN. WFSTs are nicely suited to this task but their size and run-time costs can make deployment on embedded applications challenging. In this paper, we describe the development of an on-device ITN system that is streaming, lightweight & accurate. At the core of our system is a streaming transformer tagger, that tags lexical tokens from ASR. The tag informs which ITN category might be applied, if at all. Following that, we apply an ITN-category-specific WFST, only on the tagged text, to reliably perform the ITN conversion. We show that the proposed ITN solution performs equivalent to strong baselines, while being significantly smaller in size and retaining customization capabilities., Comment: 8 pages. 6 page paper 2 page references

Automatic speech recognition (ASR) and speech translation (ST) can both use neural transducers as the model structure. It is thus possible to use a single transducer model to perform both tasks. In real-world applications, such joint ASR and ST models may need to be streaming and do not require source language identification (i.e. language-agnostic). In this paper, we propose LAMASSU, a streaming language-agnostic multilingual speech recognition and translation model using neural transducers. Based on the transducer model structure, we propose four methods, a unified joint and prediction network for multilingual output, a clustered multilingual encoder, target language identification for encoder, and connectionist temporal classification regularization. Experimental results show that LAMASSU not only drastically reduces the model size but also reaches the performances of monolingual ASR and bilingual ST models., Comment: INTERSPEECH 2023

In this paper, we introduce our work of building a Streaming Multilingual Speech Model (SM2), which can transcribe or translate multiple spoken languages into texts of the target language. The backbone of SM2 is Transformer Transducer, which has high streaming capability. Instead of human labeled speech translation (ST) data, SM2 models are trained using weakly supervised data generated by converting the transcriptions in speech recognition corpora with a machine translation service. With 351 thousand hours of anonymized speech training data from 25 languages, SM2 models achieve comparable or even better ST quality than some recent popular large-scale non-streaming speech models. More importantly, we show that SM2 has the truly zero-shot capability when expanding to new target languages, yielding high quality ST results for {source-speech, target-text} pairs that are not seen during training.

Mixed ionic‐electronic conducting (MIEC) membranes have gained growing interest recently for various promising environmental and energy applications, such as H₂ and O₂ production, CO₂ reduction, O₂ and H₂ separation, CO₂ separation, membrane reactors for production of chemicals, cathode development for solid oxide fuel cells, solar‐driven evaporation and energy‐saving regeneration as well as electrolyzer cells for power‐to‐X technologies. The purpose of this roadmap, written by international specialists in their fields, is to present a snapshot of the state‐of‐the‐art, and provide opinions on the future challenges and opportunities in this complex multidisciplinary research field. As the fundamentals of using MIEC membranes for various applications become increasingly challenging tasks, particularly in view of the growing interdisciplinary nature of this field, a better understanding of the underlying physical and chemical processes is also crucial to enable the career advancement of the next generation of researchers. As an integrated and combined article, it is hoped that this roadmap, covering all these aspects, will be informative to support further progress in academics as well as in the industry‐oriented research toward commercialization of MIEC membranes for different applications.

Typical representations for arbitrary-oriented object detection tasks include oriented bounding box (OBB), quadrilateral bounding box (QBB), and point set (PointSet). Each representation encounters problems that correspond to its characteristics, such as the boundary discontinuity, square-like problem, representation ambiguity, and isolated points, which lead to inaccurate detection. Although many effective strategies have been proposed for various representations, there is still no unified solution. Current detection methods based on Gaussian modeling have demonstrated the possibility of breaking this dilemma; however, they remain limited to OBB. To go further, in this paper, we propose a unified Gaussian representation called G-Rep to construct Gaussian distributions for OBB, QBB, and PointSet, which achieves a unified solution to various representations and problems. Specifically, PointSet or QBB-based object representations are converted into Gaussian distributions, and their parameters are optimized using the maximum likelihood estimation algorithm. Then, three optional Gaussian metrics are explored to optimize the regression loss of the detector because of their excellent parameter optimization mechanisms. Furthermore, we also use Gaussian metrics for sampling to align label assignment and regression loss. Experimental results on several public available datasets, such as DOTA, HRSC2016, UCAS-AOD, and ICDAR2015, show the excellent performance of the proposed method for arbitrary-oriented object detection., Comment: 24 pages, 6 figures, 10 tables, the code has been open sourced at https://github.com/open-mmlab/mmrotate

Neural transducers have been widely used in automatic speech recognition (ASR). In this paper, we introduce it to streaming end-to-end speech translation (ST), which aims to convert audio signals to texts in other languages directly. Compared with cascaded ST that performs ASR followed by text-based machine translation (MT), the proposed Transformer transducer (TT)-based ST model drastically reduces inference latency, exploits speech information, and avoids error propagation from ASR to MT. To improve the modeling capacity, we propose attention pooling for the joint network in TT. In addition, we extend TT-based ST to multilingual ST, which generates texts of multiple languages at the same time. Experimental results on a large-scale 50 thousand (K) hours pseudo-labeled training set show that TT-based ST not only significantly reduces inference time but also outperforms non-streaming cascaded ST for English-German translation., Comment: The paper was submitted to Interspeech 2022

Mixed ionic‐electronic conducting (MIEC) membranes have gained growing interest recently for various promising environmental and energy applications, such as H₂ and O₂ production, CO₂ reduction, O₂ and H₂ separation, CO₂ separation, membrane reactors for production of chemicals, cathode development for solid oxide fuel cells, solar‐driven evaporation and energy‐saving regeneration as well as electrolyzer cells for power‐to‐X technologies. The purpose of this roadmap, written by international specialists in their fields, is to present a snapshot of the state‐of‐the‐art, and provide opinions on the future challenges and opportunities in this complex multidisciplinary research field. As the fundamentals of using MIEC membranes for various applications become increasingly challenging tasks, particularly in view of the growing interdisciplinary nature of this field, a better understanding of the underlying physical and chemical processes is also crucial to enable the career advancement of the next generation of researchers. As an integrated and combined article, it is hoped that this roadmap, covering all these aspects, will be informative to support further progress in academics as well as in the industry‐oriented research toward commercialization of MIEC membranes for different applications.

Mixed ionic‐electronic conducting (MIEC) membranes have gained growing interest recently for various promising environmental and energy applications, such as H₂ and O₂ production, CO₂ reduction, O₂ and H₂ separation, CO₂ separation, membrane reactors for production of chemicals, cathode development for solid oxide fuel cells, solar‐driven evaporation and energy‐saving regeneration as well as electrolyzer cells for power‐to‐X technologies. The purpose of this roadmap, written by international specialists in their fields, is to present a snapshot of the state‐of‐the‐art, and provide opinions on the future challenges and opportunities in this complex multidisciplinary research field. As the fundamentals of using MIEC membranes for various applications become increasingly challenging tasks, particularly in view of the growing interdisciplinary nature of this field, a better understanding of the underlying physical and chemical processes is also crucial to enable the career advancement of the next generation of researchers. As an integrated and combined article, it is hoped that this roadmap, covering all these aspects, will be informative to support further progress in academics as well as in the industry‐oriented research toward commercialization of MIEC membranes for different applications.

Mixed ionic‐electronic conducting (MIEC) membranes have gained growing interest recently for various promising environmental and energy applications, such as H₂ and O₂ production, CO₂ reduction, O₂ and H₂ separation, CO₂ separation, membrane reactors for production of chemicals, cathode development for solid oxide fuel cells, solar‐driven evaporation and energy‐saving regeneration as well as electrolyzer cells for power‐to‐X technologies. The purpose of this roadmap, written by international specialists in their fields, is to present a snapshot of the state‐of‐the‐art, and provide opinions on the future challenges and opportunities in this complex multidisciplinary research field. As the fundamentals of using MIEC membranes for various applications become increasingly challenging tasks, particularly in view of the growing interdisciplinary nature of this field, a better understanding of the underlying physical and chemical processes is also crucial to enable the career advancement of the next generation of researchers. As an integrated and combined article, it is hoped that this roadmap, covering all these aspects, will be informative to support further progress in academics as well as in the industry‐oriented research toward commercialization of MIEC membranes for different applications.

Recently, multifold fermions characterized by band crossings with multifold degeneracy and Fermi surfaces with higher Chern numbers have been discovered experimentally in AlPt (Schroter et al. in Nat Phys 15:759–765, 2019) and XSi(X = Rh,Co) (Sanchez et al. in Nature 567:500–505, 2019; Rao et al. in Nature 567:496–499, 2019; Takane et al. in Phys Rev Lett 122:076402, 2019). In this work, we largely expand the family of multifold fermion materials by pointing out that several well-studied noncentrosymmetric superconductors are indeed multifold fermion metals. Importantly, their normal state topological properties, which have been ignored in previous studies, play an important role in the superconducting properties. Taking Li 2 Pd 3 B $\mathrm{Li} _{2}\mathrm{Pd} _{3}\mathrm{B}$ and Li 2 Pt 3 B $\mathrm{Li} _{2}\mathrm{Pt} _{3}\mathrm{B}$ as examples, we found a large number of unconventional degenerate points, such as double spin-1, spin-3/2, Weyl and double Weyl topological band crossing points near the Fermi energy, which result in finite Chern numbers on Fermi surfaces. Long Fermi arc states in Li 2 Pd 3 B $\mathrm{Li} _{2}\mathrm{Pd} _{3}\mathrm{B}$ , originating from the nontrivial band topology were found. Importantly, it has been shown experimentally that Li 2 Pd 3 B $\mathrm{Li} _{2}\mathrm{Pd} _{3}\mathrm{B}$ and Li 2 Pt 3 B $\mathrm{Li} _{2}\mathrm{Pt} _{3}\mathrm{B}$ are fully gapped and gapless superconductors, respectively. By analyzing the possible pairing symmetries, we suggest that Li 2 Pd 3 B $\mathrm{Li} _{2}\mathrm{Pd} _{3}\mathrm{B}$ is a conventional s-wave superconductor or DIII class topological superconductor with Majorana surface states. Li 2 Pt 3 B $\mathrm{Li} _{2}\mathrm{Pt} _{3}\mathrm{B}$ , being gapless, is likely to be a nodal topological superconductor with dispersionless surface Majorana modes. We further identified that several noncentrosymmetric superconductors, such as Mo 3 Al 2 C $\mathrm{Mo} _{3}\mathrm{Al} _{2}\mathrm{

We propose a method to speed up the quantum adiabatic algorithm using catalysis by many-body delocalization. This is applied to random-field antiferromagnetic Ising spin models. The algorithm is catalyzed in such a way that the evolution approximates a Heisenberg model in the middle of its course, and the model is in a delocalized phase. We show numerically that we can speed up the standard algorithm for finding the ground state of the random-field Ising model using this idea. We also demonstrate that the speedup is due to gap amplification, even though the underlying model is not frustration-free. The crossover to speedup occurs at roughly the value of the interaction which is known to be the critical one for the delocalization transition. We also calculate the participation ratio and entanglement entropy as a function of time: Their time dependencies indicate that the system is exploring more states and that they are more entangled than when there is no catalyst. Together, all these pieces of evidence demonstrate that the speedup is related to delocalization. Even though only relatively small systems can be investigated, the evidence suggests that the scaling of the method with system size is favorable. Our method is illustrated by experimental results from a small online IBM quantum computer, showing how to verify the method in future as such machines improve. The cost of the catalytic method compared with the standard algorithm is only a constant factor.

The DArk Matter Particle Explorer (DAMPE) is well suitable for searching for monochromatic and sharp $\gamma$-ray structures in the GeV$-$TeV range thanks to its unprecedented high energy resolution. In this work, we search for $\gamma$-ray line structures using five years of DAMPE data. To improve the sensitivity, we develop two types of dedicated data sets (including the BgoOnly data which is the first time to be used in the data analysis for the calorimeter-based gamma-ray observatories) and adopt the signal-to-noise ratio optimized regions of interest (ROIs) for different DM density profiles. No line signals or candidates are found between 10 and 300 GeV in the Galaxy. The constraints on the velocity-averaged cross section for $\chi\chi \to \gamma\gamma$ and the decay lifetime for $\chi \to \gamma\nu$, both at 95\% confidence level, have been calculated and the systematic uncertainties have been taken into account. Comparing to the previous Fermi-LAT results, though DAMPE has an acceptance smaller by a factor of $\sim 10$, similar constraints on the DM parameters are achieved and below 100 GeV the lower limits on the decay lifetime are even stronger by a factor of a few. Our results demonstrate the potential of high-energy-resolution observations on dark matter detection., Comment: 14 pages, 8 figures, Science Bulletin in press

The Submillimetre Common User Bolometer Array 2 (SCUBA-2) is the James Clerk Maxwell Telescope's continuum imager, operating simultaneously at 450 and 850~$\mu$m. SCUBA-2 was commissioned in 2009--2011 and since that time, regular observations of point-like standard sources have been performed whenever the instrument is in use. Expanding the calibrator observation sample by an order of magnitude compared to previous work, in this paper we derive updated opacity relations at each wavelength for a new atmospheric-extinction correction, analyze the Flux-Conversion Factors (FCFs) used to convert instrumental units to physical flux units as a function of date and observation time, present information on the beam profiles for each wavelength, and update secondary-calibrator source fluxes. Between 07:00 and 17:00 UTC, the portion of the night that is most stable to temperature gradients that cause dish deformation, the total-flux uncertainty and the peak-flux uncertainty measured at 450~$\mu$m are found to be 14\% and 17\%, respectively. Measured at 850~$\mu$m, the total-flux and peak-flux uncertainties are 6\%, and 7\%, respectively. The analysis presented in this work is applicable to all SCUBA-2 projects observed since 2011., Comment: 31 pages, 15 figures, 8 tables. This is the Accepted Manuscript version of an article accepted for publication in the Astronomical Journal. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. This Accepted Manuscript is published under a CC BY licence

Prominence plumes are evacuated upflows that emerge from bubbles below prominences, whose formation mechanism is still unclear. Here we present a detailed study of plumes in a quiescent prominence using the high-resolution H-alpha filtergrams at the line center as well as line wing at +/-0.4 angstrom from the New Vacuum Solar Telescope. Enhancements of brightening, blue shifts, and turbulence at the fronts of plumes are found during their formation. Some large plumes split at their heads and finger-shaped structures are formed between them. Blue-shifted flows along the bubble-prominence interface are found before and during the plume formation. Our observations are consistent with the hypothesis that prominence plumes are related to coupled Kelvin-Helmholtz and Rayleigh-Taylor (KH/RT) instabilities. Plume splittings and fingers are evidence of RT instability, and the flows may increase the growth rate of KH/RT instabilities. However, the significant turbulence at plume fronts may suggest that the RT instability is triggered by the plumes penetrating into the prominence. In this scenario, extra mechanisms are necessary to drive the plumes., Comment: 12 pages, 7 figures, accepted by RAA, comments are welcome to xuejc@pmo.ac.cn

We propose a method to speed up the quantum adiabatic algorithm using catalysis by many-body delocalization. This is applied to random-field antiferromagnetic Ising spin models. The algorithm is catalyzed in such a way that the evolution approximates a Heisenberg model in the middle of its course, and the model is in a delocalized phase. We show numerically that we can speed up the standard algorithm for finding the ground state of the random-field Ising model using this idea. We also demonstrate that the speedup is due to gap amplification, even though the underlying model is not frustration-free. The crossover to speedup occurs at roughly the value of the interaction which is known to be the critical one for the delocalization transition. We also calculate the participation ratio and entanglement entropy as a function of time: Their time dependencies indicate that the system is exploring more states and that they are more entangled than when there is no catalyst. Together, all these pieces of evidence demonstrate that the speedup is related to delocalization. Even though only relatively small systems can be investigated, the evidence suggests that the scaling of the method with system size is favorable. Our method is illustrated by experimental results from a small online IBM quantum computer, showing how to verify the method in future as such machines improve. The cost of the catalytic method compared with the standard algorithm is only a constant factor.

The DArk Matter Particle Explorer (DAMPE) is well suitable for searching for monochromatic and sharp $\gamma$-ray structures in the GeV$-$TeV range thanks to its unprecedented high energy resolution. In this work, we search for $\gamma$-ray line structures using five years of DAMPE data. To improve the sensitivity, we develop two types of dedicated data sets (including the BgoOnly data which is the first time to be used in the data analysis for the calorimeter-based gamma-ray observatories) and adopt the signal-to-noise ratio optimized regions of interest (ROIs) for different DM density profiles. No line signals or candidates are found between 10 and 300 GeV in the Galaxy. The constraints on the velocity-averaged cross section for $\chi\chi \to \gamma\gamma$ and the decay lifetime for $\chi \to \gamma\nu$, both at 95% confidence level, have been calculated and the systematic uncertainties have been taken into account. Comparing to the previous Fermi-LAT results, though DAMPE has an acceptance smaller by a factor of $\sim 10$, similar constraints on the DM parameters are achieved and below 100 GeV the lower limits on the decay lifetime are even stronger by a factor of a few. Our results demonstrate the potential of high-energy-resolution observations on dark matter detection., Comment: 14 pages, 8 figures. Update the content to keep up with the published version

Biogas consisting primarily of methane (CH4) and carbon dioxide (CO2) can be upgraded to a transportation fuel referred to as renewable natural gas (RNG) by removing CO2 and other impurities. RNG has energy content comparable to fossil compressed natural gas (CNG) but with lower life-cycle greenhouse gas (GHG) emissions. In this study, a light-duty cargo van was tested with CNG and two RNG blends on a chassis dynamometer in order to compare the toxicity of the resulting exhaust. Tests for reactive oxygen species (ROS), biomarker expressions (CYP1A1, IL8, COX-2), and mutagenicity (Ames) show that RNG exhaust has toxicity that is comparable or lower than CNG exhaust. Statistical analysis reveals associations between toxicity and tailpipe emissions of benzene, dibenzofuran, and dihydroperoxide dimethyl hexane (the last identification is considered tentative/uncertain). Further gas-phase toxicity may be associated with tailpipe emissions of formaldehyde, dimethyl sulfide, propene, and methyl ketene. CNG exhaust contained higher concentrations of these potentially toxic chemical constituents than RNG exhaust in all of the current tests. Photochemical aging of the vehicle exhaust did not alter these trends. These preliminary results suggest that RNG adoption may be a useful strategy to reduce the carbon intensity of transportation fuels without increasing the toxicity of the vehicle exhaust.

Dan Li,1,&ast; Xin Zhang,2,3,&ast; Yunzhong Wang,2 Jian Xue,2 Xueqiang Ji,2 Xuejun Shao,2– 4 Yang Li2– 4 1Department of Clinical Laboratory, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215004, People’s Republic of China; 2Department of Clinical Laboratory, Children’s Hospital of Soochow University, Suzhou, Jiangsu, 215025, People’s Republic of China; 3Institute of Pediatric Research, Children’s Hospital of Soochow University, Suzhou, Jiangsu, 215025, People’s Republic of China; 4Clinical Medical College of Pediatrics, Soochow University, Suzhou, Jiangsu, 215025, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yang Li; Xuejun Shao Email 11418092@zju.edu.cn; xjshao@suda.edu.cnObjective: To investigate the epidemiology and drug resistance of pathogens isolated from cerebrospinal fluid samples at a children’s medical center in eastern China and provide the basis for anti-infection treatments.Methods: In all, 307 non-duplicated strains of pathogens were isolated from cerebrospinal fluid samples in the Children’s Hospital of Soochow University from January 2006 to December 2020. Mass spectrometry was used for pathogen identification. The VITEK 2 Compact system and Kirby-Bauer method were applied to determine antimicrobial susceptibility.Results: Among the 307 isolates, gram-positive bacteria, gram-negative bacteria and fungi accounted for 60.26%, 34.53%, and 5.21%, respectively. The most prevalent pathogens were Streptococcus pneumoniae (26.06%), Escherichia coli (20.20%) and Streptococcus agalactiae (17.26%). The number of isolates was highest in winter. The most prevalent gram-positive bacterium in children < 6 months old was Streptococcus agalactiae, while Streptococcus pneumoniae was the most in children were > 6 months old. The drug resistance of gram-positive bacteria, fungi and Haemophilus influenza were not high. In addition, 35 strains of gram-negative ba

Yang Li,1– 4,&ast; Dan Li,5,&ast; Jian Xue,4 Xueqiang Ji,4 Xuejun Shao,4 Jie Yan1– 3 1Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310003, People’s Republic of China; 2Department of Medical Microbiology and Parasitology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310058, People’s Republic of China; 3Division of Basic Medical Microbiology, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310003, People’s Republic of China; 4Department of Clinical Laboratory, Children’s Hospital of Soochow University, Suzhou, Jiangsu, 215025, People’s Republic of China; 5Department of Clinical Laboratory, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215004, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jie YanDepartment of Medical Microbiology and Parasitology, Zhejiang University School of Medicine, 866 Yu-Hang-Tang Road, Hangzhou, Zhejiang, 310058, People’s Republic of ChinaTel +86-571-88208297Fax +86-571-88208294Email Med_bp@zju.edu.cnXuejun ShaoDepartment of Clinical Laboratory, Children’s Hospital of Soochow University, 92 Zhong-Nan Street, Suzhou, Jiangsu, 215025, People’s Republic of ChinaTel +86-512-80691203Email xjshao@suda.edu.cnObjective: This study investigated the epidemiology, virulence and drug resistance of invasive Klebsiella pneumoniae (K. pneumoniae) isolates at a children’s medical center in eastern China in order to obtain epidemiologic, virulence, and antimicrobial resistance data that can guide for the selection and development of anti-infection treatments.Methods: A total of 94 invasive K. pneumoniae strains were isolated from children between January 2016 and December 2020 at the Children’s Hospital of Soochow University. Th

Jian Qu,1,&ast; Hai-Hong Zhu,1,&ast; Xue-Jian Huang,1 Ge-Fei He,2 Ji-Yang Liu,2 Juan-Juan Huang,2 Ying Chen,3 Qiang Qu,4 Ya-Li Wu,5 Xiang-Yu Chen,6 Qiong Lu1 1Department of Pharmacy, the Second Xiangya Hospital, Central South University; Institute of Clinical Pharmacy, Central South University, Changsha, 410011, People’s Republic of China; 2Department of Pharmacy, The First Hospital of Changsha, Changsha, 410005, People’s Republic of China; 3Department of Pharmacy, Wuhan University, Renmin Hospital, Wuhan, 430060, People’s Republic of China; 4Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, 410007, People’s Republic of China; 5Department of Pharmacy, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, 410000, People’s Republic of China; 6Department of Radiology, the Second Xiangya Hospital, Central South University, Changsha, 410011, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Qiong LuDepartment of Pharmacy, the Second Xiangya Hospital, Central South University; Institute of Clinical Pharmacy, Central South University, 139 Middle Renmin Road, Changsha, Hunan, 410011, People’s Republic of ChinaTel +86-731-85292072Fax +86-731-85533525Email christy_luq@csu.edu.cnBackground: SARS-CoV-2 can damage not only the lungs but also the liver and kidney. Most critically ill patients with coronavirus disease 2019 (COVID-19) have liver and kidney dysfunction. We aim to investigate the levels of liver and kidney function indexes in mild and severe COVID-19 patients and their capability to predict the severity of the disease.Methods: The characteristics and laboratory indexes were compared between patients with different conditions. We applied binary logistic regression to find the independent risk factors of severe patients. Receiver operating characteristic (ROC) analysis was used to predict the severity of COVID-19 using the liver and kidney function indexes.Res

The DArk Matter Particle Explorer (DAMPE) is well suitable for searching for monochromatic and sharp $\gamma$-ray structures in the GeV$-$TeV range thanks to its unprecedented high energy resolution. In this work, we search for $\gamma$-ray line structures using five years of DAMPE data. To improve the sensitivity, we develop two types of dedicated data sets (including the BgoOnly data which is the first time to be used in the data analysis for the calorimeter-based gamma-ray observatories) and adopt the signal-to-noise ratio optimized regions of interest (ROIs) for different DM density profiles. No line signals or candidates are found between 10 and 300 GeV in the Galaxy. The constraints on the velocity-averaged cross section for $\chi\chi \to \gamma\gamma$ and the decay lifetime for $\chi \to \gamma\nu$, both at 95% confidence level, have been calculated and the systematic uncertainties have been taken into account. Comparing to the previous Fermi-LAT results, though DAMPE has an acceptance smaller by a factor of $\sim 10$, similar constraints on the DM parameters are achieved and below 100 GeV the lower limits on the decay lifetime are even stronger by a factor of a few. Our results demonstrate the potential of high-energy-resolution observations on dark matter detection., Comment: 14 pages, 8 figures. Update the content to keep up with the published version

Nearly all existing Facial Action Coding System-based datasets that include facial action unit (AU) intensity information annotate the intensity values hierarchically using A--E levels. However, facial expressions change continuously and shift smoothly from one state to another. Therefore, it is more effective to regress the intensity value of local facial AUs to represent whole facial expression changes, particularly in the fields of expression transfer and facial animation. We introduce an extension of FEAFA in combination with the relabeled DISFA database, which is available at https://www.iiplab.net/feafa+/ now. Extended FEAFA (FEAFA+) includes 150 video sequences from FEAFA and DISFA, with a total of 230,184 frames being manually annotated on floating-point intensity value of 24 redefined AUs using the Expression Quantitative Tool. We also list crude numerical results for posed and spontaneous subsets and provide a baseline comparison for the AU intensity regression task.

The DArk Matter Particle Explorer (DAMPE) is well suitable for searching for monochromatic and sharp $\gamma$-ray structures in the GeV$-$TeV range thanks to its unprecedented high energy resolution. In this work, we search for $\gamma$-ray line structures using five years of DAMPE data. To improve the sensitivity, we develop two types of dedicated data sets (including the BgoOnly data which is the first time to be used in the data analysis for the calorimeter-based gamma-ray observatories) and adopt the signal-to-noise ratio optimized regions of interest (ROIs) for different DM density profiles. No line signals or candidates are found between 10 and 300 GeV in the Galaxy. The constraints on the velocity-averaged cross section for $\chi\chi \to \gamma\gamma$ and the decay lifetime for $\chi \to \gamma\nu$, both at 95% confidence level, have been calculated and the systematic uncertainties have been taken into account. Comparing to the previous Fermi-LAT results, though DAMPE has an acceptance smaller by a factor of $\sim 10$, similar constraints on the DM parameters are achieved and below 100 GeV the lower limits on the decay lifetime are even stronger by a factor of a few. Our results demonstrate the potential of high-energy-resolution observations on dark matter detection., Comment: 14 pages, 8 figures. Update the content to keep up with the published version

The Submillimetre Common User Bolometer Array 2 (SCUBA-2) is the James Clerk Maxwell Telescope's continuum imager, operating simultaneously at 450 and 850~$\mu$m. SCUBA-2 was commissioned in 2009--2011 and since that time, regular observations of point-like standard sources have been performed whenever the instrument is in use. Expanding the calibrator observation sample by an order of magnitude compared to previous work, in this paper we derive updated opacity relations at each wavelength for a new atmospheric-extinction correction, analyze the Flux-Conversion Factors (FCFs) used to convert instrumental units to physical flux units as a function of date and observation time, present information on the beam profiles for each wavelength, and update secondary-calibrator source fluxes. Between 07:00 and 17:00 UTC, the portion of the night that is most stable to temperature gradients that cause dish deformation, the total-flux uncertainty and the peak-flux uncertainty measured at 450~$\mu$m are found to be 14\% and 17\%, respectively. Measured at 850~$\mu$m, the total-flux and peak-flux uncertainties are 6\%, and 7\%, respectively. The analysis presented in this work is applicable to all SCUBA-2 projects observed since 2011., Comment: 31 pages, 15 figures, 8 tables. This is the Accepted Manuscript version of an article accepted for publication in the Astronomical Journal. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. This Accepted Manuscript is published under a CC BY licence

Prominence plumes are evacuated upflows that emerge from bubbles below prominences, whose formation mechanism is still unclear. Here we present a detailed study of plumes in a quiescent prominence using the high-resolution H-alpha filtergrams at the line center as well as line wing at +/-0.4 angstrom from the New Vacuum Solar Telescope. Enhancements of brightening, blue shifts, and turbulence at the fronts of plumes are found during their formation. Some large plumes split at their heads and finger-shaped structures are formed between them. Blue-shifted flows along the bubble-prominence interface are found before and during the plume formation. Our observations are consistent with the hypothesis that prominence plumes are related to coupled Kelvin-Helmholtz and Rayleigh-Taylor (KH/RT) instabilities. Plume splittings and fingers are evidence of RT instability, and the flows may increase the growth rate of KH/RT instabilities. However, the significant turbulence at plume fronts may suggest that the RT instability is triggered by the plumes penetrating into the prominence. In this scenario, extra mechanisms are necessary to drive the plumes., Comment: 12 pages, 7 figures, accepted by RAA, comments are welcome to xuejc@pmo.ac.cn

We propose a method to speed up the quantum adiabatic algorithm using catalysis by many-body delocalization. This is applied to random-field antiferromagnetic Ising spin models. The algorithm is catalyzed in such a way that the evolution approximates a Heisenberg model in the middle of its course, and the model is in a delocalized phase. We show numerically that we can speed up the standard algorithm for finding the ground state of the random-field Ising model using this idea. We also demonstrate that the speedup is due to gap amplification, even though the underlying model is not frustration-free. The crossover to speedup occurs at roughly the value of the interaction which is known to be the critical one for the delocalization transition. We also calculate the participation ratio and entanglement entropy as a function of time: Their time dependencies indicate that the system is exploring more states and that they are more entangled than when there is no catalyst. Together, all these pieces of evidence demonstrate that the speedup is related to delocalization. Even though only relatively small systems can be investigated, the evidence suggests that the scaling of the method with system size is favorable. Our method is illustrated by experimental results from a small online IBM quantum computer, showing how to verify the method in future as such machines improve. The cost of the catalytic method compared with the standard algorithm is only a constant factor.

In this paper, several works are proposed to address practical challenges for deploying RNN Transducer (RNN-T) based speech recognition system. These challenges are adapting a well-trained RNN-T model to a new domain without collecting the audio data, obtaining time stamps and confidence scores at word level. The first challenge is solved with a splicing data method which concatenates the speech segments extracted from the source domain data. To get the time stamp, a phone prediction branch is added to the RNN-T model by sharing the encoder for the purpose of force alignment. Finally, we obtain word-level confidence scores by utilizing several types of features calculated during decoding and from confusion network. Evaluated with Microsoft production data, the splicing data adaptation method improves the baseline and adaptation with the text to speech method by 58.03% and 15.25% relative word error rate reduction, respectively. The proposed time stamping method can get less than 50ms word timing difference from the ground truth alignment on average while maintaining the recognition accuracy of the RNN-T model. We also obtain high confidence annotation performance with limited computation cost., Comment: 5 pages

Heatmap-based regression overcomes the lack of spatial and contextual information of direct coordinate regression, and has revolutionized the task of face alignment. Yet it suffers from quantization errors caused by neglecting subpixel coordinates in image resizing and network downsampling. In this paper, we first quantitatively analyze the quantization error on benchmarks, which accounts for more than 1/3 of the whole prediction errors for state-of-the-art methods. To tackle this problem, we propose a novel Heatmap In Heatmap(HIH) representation and a coordinate soft-classification (CSC) method, which are seamlessly integrated into the classic hourglass network. The HIH representation utilizes nested heatmaps to jointly represent the coordinate label: one heatmap called integer heatmap stands for the integer coordinate, and the other heatmap named decimal heatmap represents the subpixel coordinate. The range of a decimal heatmap makes up one pixel in the corresponding integer heatmap. Besides, we transfer the offset regression problem to an interval classification task, and CSC regards the confidence of the pixel as the probability of the interval. Meanwhile, CSC applying the distribution loss leverage the soft labels generated from the Gaussian distribution function to guide the offset heatmap training, which makes it easier to learn the distribution of coordinate offsets. Extensive experiments on challenging benchmark datasets demonstrate that our HIH can achieve state-of-the-art results. In particular, our HIH reaches 4.08 NME (Normalized Mean Error) on WFLW, and 3.21 on COFW, which exceeds previous methods by a significant margin., Comment: A large update(v2) for HIH