Multi-Domain Active Learning: A Comparative Study

Building classifiers on multiple domains is a practical problem in the real life. Instead of building classifiers one by one, multi-domain learning (MDL) simultaneously builds classifiers on multiple domains. MDL utilizes the information shared among the domains to improve the performance. As a supervised learning problem, the labeling effort is still high in MDL problems. Usually, this high labeling cost issue could be relieved by using active learning. Thus, it is natural to utilize active learning to reduce the labeling effort in MDL, and we refer this setting as multi-domain active learning (MDAL). However, there are only few works which are built on this setting. And when the researches have to face this problem, there is no off-the-shelf solutions. Under this circumstance, combining the current multi-domain learning models and single-domain active learning strategies might be a preliminary solution for MDAL problem. To find out the potential of this preliminary solution, a comparative study over 5 models and 4 selection strategies is made in this paper. To the best of our knowledge, this is the first work provides the formal definition of MDAL. Besides, this is the first comparative work for MDAL problem. From the results, the Multinomial Adversarial Networks (MAN) model with a simple best vs second best (BvSB) uncertainty strategy shows its superiority in most cases. We take this combination as our off-the-shelf recommendation for the MDAL problem

Multi-Domain Learning From Insufficient Annotations

Multi-domain learning (MDL) refers to simultaneously constructing a model or a set of models on datasets collected from different domains. Conventional approaches emphasize domain-shared information extraction and domain-private information preservation, following the shared-private framework (SP models), which offers significant advantages over single-domain learning. However, the limited availability of annotated data in each domain considerably hinders the effectiveness of conventional supervised MDL approaches in real-world applications. In this paper, we introduce a novel method called multi-domain contrastive learning (MDCL) to alleviate the impact of insufficient annotations by capturing both semantic and structural information from both labeled and unlabeled data.Specifically, MDCL comprises two modules: inter-domain semantic alignment and intra-domain contrast. The former aims to align annotated instances of the same semantic category from distinct domains within a shared hidden space, while the latter focuses on learning a cluster structure of unlabeled instances in a private hidden space for each domain. MDCL is readily compatible with many SP models, requiring no additional model parameters and allowing for end-to-end training. Experimental results across five textual and image multi-domain datasets demonstrate that MDCL brings noticeable improvement over various SP models.Furthermore, MDCL can further be employed in multi-domain active learning (MDAL) to achieve a superior initialization, eventually leading to better overall performance.Comment: This paper has been accepted to ECAI-2

Dynamic changes and convergence of China’s regional green productivity:A dynamic spatial econometric analysis

Low-carbon economic development is at the heart of the post-pandemic green recovery scheme worldwide. It requires economic recovery without compromising on the environment, implying a critical role that green productivity plays in achieving the carbon neutrality goal. Green productivity measures the quality of economic growth with consideration for energy consumption and environmental pollution. This study employs the slacks-based measure directional distance function (SBM-DDF) approach and the Malmquist-Luenberger (ML) index to calculate green productivity and its components of 30 provinces in China between 2001 and 2018. Using a spatial panel data model, we empirically analyzed the conditional β-convergence of China's green productivity. We found that overall, since 2001, China's green productivity has demonstrated a continuous upward trend. When taking into account spatial factors, China's green productivity demonstrates a significant conditional β-convergence. In terms of regional effects, the results indicate that the green productivity of the eastern and western regions demonstrates club convergence, implying a more balanced green economic development. Moreover, the convergence rate of China's green productivity increases with the addition of environmental regulation variable, and so the corresponding convergence time decreases. It indicates that environmental regulations help to facilitate the convergence of China's green productivity, narrowing the gap between the regional green economic development. The findings provide guideline for achieving a low-carbon development and carbon neutrality from a regional green productivity perspective

Impact of internal mammary artery perforator propeller flaps combined with radiotherapy in the treatment of large chest keloids: Our experience

BackgroundKeloids are benign skin hyperplasias but have a tumor-like appearance. Clinical management of keloids remains challenging.AimsWe retrospectively evaluated the safety and efficacy of internal mammary artery perforator propeller flaps combined with timely radiotherapy in the treatment of large chest keloids.MethodsFrom June 2017 to May 2020, 25 patients with large chest keloids (average size 4.82 cm ± 2.53 cm × 9.04 cm ± 4.86 cm) who received both radiotherapy and internal mammary artery perforator flaps transplantation in our department were included. After surgical removal of the keloids, various propeller flaps based on the unilateral internal mammary artery were designed and applied to repair the defects. Timely and full-dose radiotherapy was performed for these patients after the operation.ResultsAfter keloid resection, the dimensions of the defect area were 3 cm–15 cm × 4 cm–25 cm, and the sizes of the flaps were 3 cm–16 cm × 4 cm–27 cm. For all 25 patients, the flaps survived, and the incisions healed in one stage. During the follow-up (median 18 months), no local recurrence was observed, and the itching and pain symptoms in the scar area were significantly relieved. Both physicians and patients were satisfied with the results.ConclusionsThe application of internal mammary artery perforator propeller flaps combined with radiotherapy in the treatment of chest keloids can effectively reduce the recurrence of keloids and relieve the related symptoms. It also has advantages including minimized donor site damage, short operation time and speedy postoperative recovery, suggesting its great clinical value

RepLong - de novo repeat identification using long read sequencing data

Abstract Motivation The identification of repetitive elements is important in genome assembly and phylogenetic analyses. The existing de novo repeat identification methods exploiting the use of short reads are impotent in identifying long repeats. Since long reads are more likely to cover repeat regions completely, using long reads is more favorable for recognizing long repeats. Results In this study, we propose a novel de novo repeat elements identification method namely RepLong based on PacBio long reads. Given that the reads mapped to the repeat regions are highly overlapped with each other, the identification of repeat elements is equivalent to the discovery of consensus overlaps between reads, which can be further cast into a community detection problem in the network of read overlaps. In RepLong, we first construct a network of read overlaps based on pair-wise alignment of the reads, where each vertex indicates a read and an edge indicates a substantial overlap between the corresponding two reads. Secondly, the communities whose intra connectivity is greater than the inter connectivity are extracted based on network modularity optimization. Finally, representative reads in each community are extracted to form the repeat library. Comparison studies on Drosophila melanogaster and human long read sequencing data with genome-based and short-read-based methods demonstrate the efficiency of RepLong in identifying long repeats. RepLong can handle lower coverage data and serve as a complementary solution to the existing methods to promote the repeat identification performance on long-read sequencing data. Availability and implementation The software of RepLong is freely available at https://github.com/ruiguo-bio/replong. Supplementary information Supplementary data are available at Bioinformatics online. </jats:sec

Individual-based morphological brain network organization and its association with autistic symptoms in young children with autism spectrum disorder

Individual-based morphological brain networks built from T1-weighted magnetic resonance imaging (MRI) reflect synchronous maturation intensities between anatomical regions at the individual level. Autism spectrum disorder (ASD) is a socio-cognitive and neurodevelopmental disorder with high neuroanatomical heterogeneity, but the specific patterns of morphological networks in ASD remain largely unexplored at the individual level. In this study, individual-based morphological networks were constructed by using high-resolution structural MRI data from 40 young children with ASD (age range: 2-8 years) and 38 age-, gender-, and handedness-matched typically developing children (TDC). Measurements were recorded as threefold. Results showed that compared with TDC, young children with ASD exhibited lower values of small-worldness (i.e., sigma) of individual-level morphological brain networks, increased morphological connectivity in cortico-striatum-thalamic-cortical (CSTC) circuitry, and decreased morphological connectivity in the cortico-cortical network. In addition, morphological connectivity abnormalities can predict the severity of social communication deficits in young children with ASD, thus confirming an associational impact at the behavioral level. These findings suggest that the morphological brain network in the autistic developmental brain is inefficient in segregating and distributing information. The results also highlight the crucial role of abnormal morphological connectivity patterns in the socio-cognitive deficits of ASD and support the possible use of the aberrant developmental patterns of morphological brain networks in revealing new clinically-relevant biomarkers for ASD.China Postdoctoral Science Foundation, Grant/Award Number: 2019M660236; National Natural Science Foundation of China, Grant/Award Numbers: 61901129, 62036003, 81871432, U1808204; The Basque Foundation for Science and from Ministerio de Economia, Industria y Competitividad (Spain) and FEDER, Grant/Award Number: DPI2016-79874-R; the Fundamental Research Funds for the Central Universities, Grant/Award Numbers: 2672018ZYGX2018J079, ZYGX2019Z017; the Sichuan Science and Technology Program, Grant/Award Number: 2019YJ018

Observation of nonrelativistic plaid-like spin splitting in a noncoplanar antiferromagnet

Spatial, momentum and energy separation of electronic spins in condensed matter systems guides the development of novel devices where spin-polarized current is generated and manipulated. Recent attention on a set of previously overlooked symmetry operations in magnetic materials leads to the emergence of a new type of spin splitting besides the well-studied Zeeman, Rashba and Dresselhaus effects, enabling giant and momentum dependent spin polarization of energy bands on selected antiferromagnets independent of relativistic spin-orbit interaction. Despite the ever-growing theoretical predictions, the direct spectroscopic proof of such spin splitting is still lacking. Here, we provide solid spectroscopic and computational evidence for the existence of such materials. In the noncoplanar antiferromagnet MnTe$_2$, the in-plane components of spin are found to be antisymmetric about the high-symmetry planes of the Brillouin zone, comprising a plaid-like spin texture in the antiferromagnetic ground state. Such an unconventional spin pattern, further found to diminish at the high-temperature paramagnetic state, stems from the intrinsic antiferromagnetic order instead of the relativistic spin-orbit coupling. Our finding demonstrates a new type of spin-momentum locking with a nonrelativistic origin, placing antiferromagnetic spintronics on a firm basis and paving the way for studying exotic quantum phenomena in related materials.Comment: Version 2, 30 pages, 4 main figures and 8 supporting figure