Domain-invariant Feature Exploration for Domain Generalization

Deep learning has achieved great success in the past few years. However, the performance of deep learning is likely to impede in face of non-IID situations. Domain generalization (DG) enables a model to generalize to an unseen test distribution, i.e., to learn domain-invariant representations. In this paper, we argue that domain-invariant features should be originating from both internal and mutual sides. Internal invariance means that the features can be learned with a single domain and the features capture intrinsic semantics of data, i.e., the property within a domain, which is agnostic to other domains. Mutual invariance means that the features can be learned with multiple domains (cross-domain) and the features contain common information, i.e., the transferable features w.r.t. other domains. We then propose DIFEX for Domain-Invariant Feature EXploration. DIFEX employs a knowledge distillation framework to capture the high-level Fourier phase as the internally-invariant features and learn cross-domain correlation alignment as the mutually-invariant features. We further design an exploration loss to increase the feature diversity for better generalization. Extensive experiments on both time-series and visual benchmarks demonstrate that the proposed DIFEX achieves state-of-the-art performance.Comment: Accepted by Transactions on Machine Learning Research (TMLR) 2022; 20 pages; code: https://github.com/jindongwang/transferlearning/tree/master/code/DeepD

Attentional Prototype Inference for Few-Shot Segmentation

This paper aims to address few-shot segmentation. While existing prototype-based methods have achieved considerable success, they suffer from uncertainty and ambiguity caused by limited labeled examples. In this work, we propose attentional prototype inference (API), a probabilistic latent variable framework for few-shot segmentation. We define a global latent variable to represent the prototype of each object category, which we model as a probabilistic distribution. The probabilistic modeling of the prototype enhances the model's generalization ability by handling the inherent uncertainty caused by limited data and intra-class variations of objects. To further enhance the model, we introduce a local latent variable to represent the attention map of each query image, which enables the model to attend to foreground objects while suppressing the background. The optimization of the proposed model is formulated as a variational Bayesian inference problem, which is established by amortized inference networks. We conduct extensive experiments on four benchmarks, where our proposal obtains at least competitive and often better performance than state-of-the-art prototype-based methods. We also provide comprehensive analyses and ablation studies to gain insight into the effectiveness of our method for few-shot segmentation.Comment: Pattern Recognition Journa

In Silico Discovery of JMJD6 Inhibitors for Cancer Treatment.

The 2-oxoglutarate (2OG)-dependent oxygenase JMJD6 is emerging as a potential anticancer target, but its inhibitors have not been reported so far. In this study, we reported an in silico protocol to discover JMJD6 inhibitors targeting the druggable 2OG-binding site. Following this protocol, one compound, which we named as WL12, was found to be able to inhibit JMJD6 enzymatic activity and JMJD6-dependent cell proliferation. To our best knowledge, this is the first case in drug discovery targeting JMJD6

Effect of mangrove species on removal of tetrabromobisphenol A from contaminated sediments.

The increase levels of tetrabromobisphenol A (TBBPA) in mangrove wetlands is of concern due to its potential toxic impacts on ecosystem. A 93-day greenhouse pot experiment was conducted to investigate the effects of mangrove plants, A. marina and K. obovata, on TBBPA degradation in sediment and to reveal the associated contributing factor(s) for its degradation. Results show that both mangrove species could uptake, translocate, and accumulate TBBPA from mangrove sediments. Compared to the unplanted sediment, urease and dehydrogenase activity as well as total bacterial abundance increased significantly (p < 0.05) in the sediment planted with mangrove plants, especially for K. obovata. In the mangrove-planted sediment, the Anaerolineae genus was the dominant bacteria, which has been reported to enhance TBBPA dissipation, and its abundance increased significantly in the sediment at early stage (0-35 day) of the greenhouse experiment. Compared to A. marina-planted sediment, higher enrichment of Geobater, Pseudomonas, Flavobacterium, Azoarcus, all of which could stimulate TBBPA degradation, was observed for the K. obovata-planted sediment during the 93-day growth period. Our mass balance result has suggested that plant-induced TBBPA degradation in the mangrove sediment is largely due to elevated microbial activities and total bacterial abundance in the rhizosphere, rather than plant uptake. In addition, different TBBPA removal efficiencies were observed in the sediments planted with different mangrove species. This study has demonstrated that K. obovata is a more suitable mangrove species than A. marina when used for remediation of TBBPA-contaminated sediment

Terrestrial-derived soil protein in coastal water: metal sequestration mechanism and ecological function.

Terrestrial fungi, especially arbuscular mycorrhizal (AM) fungi, enhance heavy metal sequestration and promote ecosystem restoration. However, their ecological functions were historically overlooked in discussions regarding water quality. As an AM fungi-derived stable soil protein fraction, glomalin-related soil protein (GRSP) may provide insights into the ecological functions of AM fungi associated with water quality in coastal ecosystems. Here, we first assessed the metal-loading dynamics and ecological functions of GRSP transported into aquatic ecosystems, characterized the composition characteristics, and revealed the mechanisms underlying Cu and Cd sequestration. Combining in situ sampling and in vitro cultures, we found that the composition characteristics of GRSP were significantly affected by the element and mineral composition of sediments. In situ, GRSP-bound Cu and Cd contributed 18.91-22.03% of the total Cu and 2.27-6.37% of the total Cd. Functional group ligands and ion exchange were the principal mechanisms of Cu binding by GRSP, while Cd binding was dominated by functional group ligands. During the in vitro experiment, GRSP sequestered large amounts of Cu and Cd and formed stable complexes, while further dialysis only released 25.74 ± 3.85% and 33.53 ± 3.62% of GRSP-bound Cu and Cd, respectively

Effect of mangrove species on removal of tetrabromobisphenol A from contaminated sediments

Abstract(#br)The increase levels of tetrabromobisphenol A (TBBPA) in mangrove wetlands is of concern due to its potential toxic impacts on ecosystem. A 93-day greenhouse pot experiment was conducted to investigate the effects of mangrove plants, A. marina and K. obovata , on TBBPA degradation in sediment and to reveal the associated contributing factor(s) for its degradation. Results show that both mangrove species could uptake, translocate, and accumulate TBBPA from mangrove sediments. Compared to the unplanted sediment, urease and dehydrogenase activity as well as total bacterial abundance increased significantly ( p < 0.05) in the sediment planted with mangrove plants, especially for K. obovata . In the mangrove-planted sediment, the Anaerolineae genus was the dominant bacteria, which has been reported to enhance TBBPA dissipation, and its abundance increased significantly in the sediment at early stage (0–35 day) of the greenhouse experiment. Compared to A. marina -planted sediment, higher enrichment of Geobater, Pseudomonas, Flavobacterium, Azoarcus , all of which could stimulate TBBPA degradation, was observed for the K. obovata -planted sediment during the 93-day growth period. Our mass balance result has suggested that plant-induced TBBPA degradation in the mangrove sediment is largely due to elevated microbial activities and total bacterial abundance in the rhizosphere, rather than plant uptake. In addition, different TBBPA removal efficiencies were observed in the sediments planted with different mangrove species. This study has demonstrated that K. obovata is a more suitable mangrove species than A. marina when used for remediation of TBBPA-contaminated sediment

Terrestrial-derived soil protein in coastal water: Metal sequestration mechanism and ecological function

Abstract(#br)Terrestrial fungi, especially arbuscular mycorrhizal (AM) fungi, enhance heavy metal sequestration and promote ecosystem restoration. However, their ecological functions were historically overlooked in discussions regarding water quality. As an AM fungi-derived stable soil protein fraction, glomalin-related soil protein (GRSP) may provide insights into the ecological functions of AM fungi associated with water quality in coastal ecosystems. Here, we first assessed the metal-loading dynamics and ecological functions of GRSP transported into aquatic ecosystems, characterized the composition characteristics, and revealed the mechanisms underlying Cu and Cd sequestration. Combining in situ sampling and in vitro cultures, we found that the composition characteristics of GRSP were significantly affected by the element and mineral composition of sediments. In situ , GRSP-bound Cu and Cd contributed 18.91–22.03% of the total Cu and 2.27–6.37% of the total Cd. Functional group ligands and ion exchange were the principal mechanisms of Cu binding by GRSP, while Cd binding was dominated by functional group ligands. During the in vitro experiment, GRSP sequestered large amounts of Cu and Cd and formed stable complexes, while further dialysis only released 25.74 ± 3.85% and 33.53 ± 3.62% of GRSP-bound Cu and Cd, respectively