MLNet: Mutual Learning Network with Neighborhood Invariance for Universal Domain Adaptation

Universal domain adaptation (UniDA) is a practical but challenging problem, in which information about the relation between the source and the target domains is not given for knowledge transfer. Existing UniDA methods may suffer from the problems of overlooking intra-domain variations in the target domain and difficulty in separating between the similar known and unknown class. To address these issues, we propose a novel Mutual Learning Network (MLNet) with neighborhood invariance for UniDA. In our method, confidence-guided invariant feature learning with self-adaptive neighbor selection is designed to reduce the intra-domain variations for more generalizable feature representation. By using the cross-domain mixup scheme for better unknown-class identification, the proposed method compensates for the misidentified known-class errors by mutual learning between the closed-set and open-set classifiers. Extensive experiments on three publicly available benchmarks demonstrate that our method achieves the best results compared to the state-of-the-arts in most cases and significantly outperforms the baseline across all the four settings in UniDA. Code is available at https://github.com/YanzuoLu/MLNet.Comment: Accepted by AAAI 2024 (Poster

Is eating raisins healthy?

Raisins are dried grapes consumed worldwide that contain beneficial components for human health. They are rich in fiber and phytochemicals such as phenolic compounds. Despite a 60% sugar content, several studies have reported health-promoting properties for raisins and this review compiles the intervention studies, as well as the cell line and animal model studies carried out to date. It has been demonstrated that raisins possess a low-to-moderate glycemic index, which makes them a healthy snack. They seem to contribute to a better diet quality and may reduce appetite. Their antioxidant capacity has been correlated to the phenolic content and this may be involved in the improvement of cardiovascular health. In addition, raisins maintain a good oral health due to their antibacterial activity, low adherence to teeth and an optimum oral pH. Raisin consumption also seems to be favorable for colon function, although more studies should be done to conclude this benefit. Moreover, gut microbiota could be affected by the prebiotic content of raisins. Cell line and animal model studies show other potential benefits in specific diseases, such as cancer and Alzheimer's disease. However, deeper research is required and future intervention studies with humans are needed. Overall, incorporating an 80-90 g portion of raisins (half a cup) into the daily diet may be favorable for human health

Bilingually motivated word segmentation for statistical machine translation

We introduce a bilingually motivated word segmentation approach to languages where word boundaries are not orthographically marked, with application to Phrase-Based Statistical Machine Translation (PB-SMT). Our approach is motivated from the insight that PB-SMT systems can be improved by optimizing the input representation to reduce the predictive power of translation models. We firstly present an approach to optimize the existing segmentation of both source and target languages for PB-SMT and demonstrate the effectiveness of this approach using a Chinese–English MT task, that is, to measure the influence of the segmentation on the performance of PB-SMT systems. We report a 5.44% relative increase in Bleu score and a consistent increase according to other metrics. We then generalize this method for Chinese word segmentation without relying on any segmenters and show that using our segmentation PB-SMT can achieve more consistent state-of-the-art performance across two domains. There are two main advantages of our approach. First of all, it is adapted to the specific translation task at hand by taking the corresponding source (target) language into account. Second, this approach does not rely on manually segmented training data so that it can be automatically adapted for different domains

The characteristic blue spectra of accretion disks in quasars as uncovered in the infrared

Quasars are thought to be powered by supermassive black holes accreting surrounding gas. Central to this picture is a putative accretion disk which is believed to be the source of the majority of the radiative output. It is well known, however, that the most extensively studied disk model -- an optically thick disk which is heated locally by the dissipation of gravitational binding energy -- is apparently contradicted by observations in a few major respects. In particular, the model predicts a specific blue spectral shape asymptotically from the visible to the near-infrared, but this is not generally seen in the visible wavelength region where the disk spectrum is observable. A crucial difficulty was that, toward the infrared, the disk spectrum starts to be hidden under strong hot dust emission from much larger but hitherto unresolved scales, and thus has essentially been impossible to observe. Here we report observations of polarized light interior to the dust-emiting region that enable us to uncover this near-infrared disk spectrum in several quasars. The revealed spectra show that the near-infrared disk spectrum is indeed as blue as predicted. This indicates that, at least for the outer near-infrared-emitting radii, the standard picture of the locally heated disk is approximately correct. The model problems at shorter wavelengths should then be directed toward a better understanding of the inner parts of the revealed disk. The newly uncovered disk emission at large radii, with more future measurements, will also shed totally new light on the unanswered critical question of how and where the disk ends.Comment: published in Nature, 24 July 2008 issue. Supplementary Information can be found at http://www.mpifr-bonn.mpg.de/div/ir-interferometry/suppl_info.pdf Published version can be accessed from http://www.nature.com/nature/journal/v454/n7203/pdf/nature07114.pd

The MASSIVE Survey. VI. The spatial sistribution and kinematics of warm ionized gas in the most massive local early-type galaxies

We present the first systematic investigation of the existence, spatial distribution, and kinematics of warm ionized gas as traced by the [O ii] 3727 Å emission line in 74 of the most massive galaxies in the local universe. All of our galaxies have deep integral-field spectroscopy from the volume- and magnitude-limited MASSIVE survey of early-type galaxies with stellar mass $\mathrm{log}({M}_{* }/{M}_{\odot })\gt 11.5$ (M K < −25.3 mag) and distance D < 108 Mpc. Of the 74 galaxies in our sample, we detect warm ionized gas in 28, which yields a global detection fraction of 38 ± 6% down to a typical [O ii] equivalent width limit of 2 Å. MASSIVE fast rotators are more likely to have gas than MASSIVE slow rotators with detection fractions of 80 ± 10% and 28 ± 6%, respectively. The spatial extents span a wide range of radii (0.6–18.2 kpc; 0.1–4R e ), and the gas morphologies are diverse, with 17/28 ≈ 61 ± 9% being centrally concentrated, 8/28 ≈ 29 ± 9% exhibiting clear rotation out to several kiloparsecs, and 3/28 ≈ 11 ± 6% being extended but patchy. Three out of four fast rotators show kinematic alignment between the stars and gas, whereas the two slow rotators with robust kinematic measurements available exhibit kinematic misalignment. Our inferred warm ionized gas masses are roughly ~105 M ⊙. The emission line ratios and radial equivalent width profiles are generally consistent with excitation of the gas by the old underlying stellar population. We explore different gas origin scenarios for MASSIVE galaxies and find that a variety of physical processes are likely at play, including internal gas recycling, cooling out of the hot gaseous halo, and gas acquired via mergers

Soil methane sink capacity response to a long-term wildfire chronosequence in Northern Sweden

Boreal forests occupy nearly one fifth of the terrestrial land surface and are recognised as globally important regulators of carbon (C) cycling and greenhouse gas emissions. Carbon sequestration processes in these forests include assimilation of CO2 into biomass and subsequently into soil organic matter, and soil microbial oxidation of methane (CH4). In this study we explored how ecosystem retrogression, which drives vegetation change, regulates the important process of soil CH4 oxidation in boreal forests. We measured soil CH4 oxidation processes on a group of 30 forested islands in northern Sweden differing greatly in fire history, and collectively representing a retrogressive chronosequence, spanning 5000 years. Across these islands the build-up of soil organic matter was observed to increase with time since fire disturbance, with a significant correlation between greater humus depth and increased net soil CH4 oxidation rates. We suggest that this increase in net CH4 oxidation rates, in the absence of disturbance, results as deeper humus stores accumulate and provide niches for methanotrophs to thrive. By using this gradient we have discovered important regulatory controls on the stability of soil CH4 oxidation processes that could not have not been explored through shorter-term experiments. Our findings indicate that in the absence of human interventions such as fire suppression, and with increased wildfire frequency, the globally important boreal CH4 sink could be diminished

Abnormal cognition, sleep, EEG and brain metabolism in a novel knock-in Alzheimer mouse, PLB1

Peer reviewedPublisher PD