347 research outputs found
CEIL: A General Classification-Enhanced Iterative Learning Framework for Text Clustering
Text clustering, as one of the most fundamental challenges in unsupervised
learning, aims at grouping semantically similar text segments without relying
on human annotations. With the rapid development of deep learning, deep
clustering has achieved significant advantages over traditional clustering
methods. Despite the effectiveness, most existing deep text clustering methods
rely heavily on representations pre-trained in general domains, which may not
be the most suitable solution for clustering in specific target domains. To
address this issue, we propose CEIL, a novel Classification-Enhanced Iterative
Learning framework for short text clustering, which aims at generally promoting
the clustering performance by introducing a classification objective to
iteratively improve feature representations. In each iteration, we first adopt
a language model to retrieve the initial text representations, from which the
clustering results are collected using our proposed Category Disentangled
Contrastive Clustering (CDCC) algorithm. After strict data filtering and
aggregation processes, samples with clean category labels are retrieved, which
serve as supervision information to update the language model with the
classification objective via a prompt learning approach. Finally, the updated
language model with improved representation ability is used to enhance
clustering in the next iteration. Extensive experiments demonstrate that the
CEIL framework significantly improves the clustering performance over
iterations, and is generally effective on various clustering algorithms.
Moreover, by incorporating CEIL on CDCC, we achieve the state-of-the-art
clustering performance on a wide range of short text clustering benchmarks
outperforming other strong baseline methods.Comment: The Web Conference 202
Epigenetic regulation of sulfur homeostasis in plants
Plants have evolved sophisticated mechanisms for adaptation to fluctuating availability of nutrients in soil. Such mechanisms are of importance for plants to maintain homeostasis of nutrient elements for their development and growth. The molecular mechanisms controlling the homeostasis of nutrient elements at the genetic level have been gradually revealed, including the identification of regulatory factors and transporters responding to nutrient stresses. Recent studies have suggested that such responses are controlled not only by genetic regulation but also by epigenetic regulation. In this review, we present recent studies on the involvement of DNA methylation, histone modifications, and non-coding RNA-mediated gene silencing in the regulation of sulfur homeostasis and the response to sulfur deficiency. We also discuss the potential effect of sulfur-containing metabolites such as S-adenosylmethionine on the maintenance of DNA and histone methylation
InterFace:Adjustable Angular Margin Inter-class Loss for Deep Face Recognition
In the field of face recognition, it is always a hot research topic to
improve the loss solution to make the face features extracted by the network
have greater discriminative power. Research works in recent years has improved
the discriminative power of the face model by normalizing softmax to the cosine
space step by step and then adding a fixed penalty margin to reduce the
intra-class distance to increase the inter-class distance. Although a great
deal of previous work has been done to optimize the boundary penalty to improve
the discriminative power of the model, adding a fixed margin penalty to the
depth feature and the corresponding weight is not consistent with the pattern
of data in the real scenario. To address this issue, in this paper, we propose
a novel loss function, InterFace, releasing the constraint of adding a margin
penalty only between the depth feature and the corresponding weight to push the
separability of classes by adding corresponding margin penalties between the
depth features and all weights. To illustrate the advantages of InterFace over
a fixed penalty margin, we explained geometrically and comparisons on a set of
mainstream benchmarks. From a wider perspective, our InterFace has advanced the
state-of-the-art face recognition performance on five out of thirteen
mainstream benchmarks. All training codes, pre-trained models, and training
logs, are publicly released
\footnote{}.Comment: arXiv admin note: text overlap with arXiv:2109.09416 by other author
Experimental study on control of Limnoperna fortunei biofouling in water transfer tunnels
The golden mussel (Limnoperna fortunei) is a filter-collector macroinvertebrate species originating from southern China. It easily invades water transfer tunnels and attaches onto tunnel walls and structures with extremely high density, resulting in biofouling, pipe clogging, structure corrosion, a decrease in water transfer efficiency, and water pollution. It has become a prevalent problem and has caused concern all over the world. However, an effective and environment friendly method of controlling golden mussel invasion has not yet been approved. This study is aimed to propose measures for preventing golden mussel invasion and biofouling in the water transfer tunnels of the East River Water Source Project (ERWSP), which transfers water from the East River to Shenzhen, southern China for 10 million people. Long-term samplings and observations of the East River water were performed to study the golden mussel's invading pattern. Flume experiments were done to study the golden mussel's attachment on 14 different materials and performance in turbulent flows. An integrated ecological prevention pool was designed and constructed based on the flume experimental results for preventing the golden mussel invasion in the scale model tunnels of the ERWSP. The major technology of the ecological pool was preventing the golden mussel from entering the tunnels by attracting veligers to attach on geotextile cloth, attracting mussels to attach on bamboo, and killing veligers with high-frequency turbulence. An eight-month application experiment showed that the ecological pool successfully controlled the golden mussel invasion and biofouling in the scale model tunnels. The mussel density on the attachment materials decreased sharply as the distance of the materials from the pool entrance increased; the turbulence was effective in killing veligers that escaped from the attachment materials. No mussel was found on the model tunnels. Thus, the integrated ecological prevention pool is recommended as a successful measure for controlling the golden mussel invasion and biofouling in water transfer tunnels.Facultad de Ciencias Naturales y Muse
Activation of EDTA-resistant gelatinases in malignant human tumors
Among the many proteases associated with human cancer, seprase or fibroblast activation protein alpha, a type II transmembrane glycoprotein, has two types of EDTA-resistant protease activities: dipeptidyl peptidase and a 170-kDa gelatinase activity. To test if activation of gelatinases associated with seprase could be involved in malignant tumors, we used a mammalian expression system to generate a soluble recombinant seprase (r-seprase). In the presence of putative EDTA-sensitive activators, r-seprase was converted into 70- to 50-kDa shortened forms of seprase (s-seprase), which exhibited a 7-fold increase in gelatinase activity, whereas levels of dipeptidyl peptidase activity remained unchanged. In malignant human tumors, seprase is expressed predominantly in tumor cells as shown by in situ hybridization and immunohistochemistry. Proteins purified from experimental xenografts and malignant tumors using antibody- or lectin-affinity columns in the presence of 5 mmol/L EDTA were assayed for seprase activation in vivo. Seprase expression and activation occur most prevalently in ovarian carcinoma but were also detected in four other malignant tumor types, including adenocarcinoma of the colon and stomach, invasive ductal carcinoma of the breast, and malignant melanoma. Together, these data show that, in malignant tumors, seprase is proteolytically activated to confer its substrate specificity in collagen proteolysis and tumor invasion
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Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use.
Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures
Seizing the window of opportunity to mitigate the impact of climate change on the health of Chinese residents
The health threats posed by climate change in China are increasing rapidly. Each province faces different health risks. Without a timely and adequate response, climate change will impact lives and livelihoods at an accelerated rate and even prevent the achievement of the Healthy and Beautiful China initiatives. The 2021 China Report of the Lancet Countdown on Health and Climate Change is the first annual update of China’s Report of the Lancet Countdown. It comprehensively assesses the impact of climate change on the health of Chinese households and the measures China has taken. Invited by the Lancet committee, Tsinghua University led the writing of the report and cooperated with 25 relevant institutions in and outside of China. The report includes 25 indicators within five major areas (climate change impacts, exposures, and vulnerability; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement) and a policy brief. This 2021 China policy brief contains the most urgent and relevant indicators focusing on provincial data: The increasing health risks of climate change in China; mixed progress in responding to climate change. In 2020, the heatwave exposures per person in China increased by 4.51 d compared with the 1986–2005 average, resulting in an estimated 92% increase in heatwave-related deaths. The resulting economic cost of the estimated 14500 heatwave-related deaths in 2020 is US$176 million. Increased temperatures also caused a potential 31.5 billion h in lost work time in 2020, which is equivalent to 1.3% of the work hours of the total national workforce, with resulting economic losses estimated at 1.4% of China’s annual gross domestic product. For adaptation efforts, there has been steady progress in local adaptation planning and assessment in 2020, urban green space growth in 2020, and health emergency management in 2019. 12 of 30 provinces reported that they have completed, or were developing, provincial health adaptation plans. Urban green space, which is an important heat adaptation measure, has increased in 18 of 31 provinces in the past decade, and the capacity of China’s health emergency management increased in almost all provinces from 2018 to 2019. As a result of China’s persistent efforts to clean its energy structure and control air pollution, the premature deaths due to exposure to ambient particulate matter of 2.5 μm or less (PM2.5) and the resulting costs continue to decline. However, 98% of China’s cities still have annual average PM2.5 concentrations that are more than the WHO guideline standard of 10 μg/m3. It provides policymakers and the public with up-to-date information on China’s response to climate change and improvements in health outcomes and makes the following policy recommendations. (1) Promote systematic thinking in the related departments and strengthen multi-departmental cooperation. Sectors related to climate and development in China should incorporate health perspectives into their policymaking and actions, demonstrating WHO’s and President Xi Jinping’s so-called health-in-all-policies principle. (2) Include clear goals and timelines for climate-related health impact assessments and health adaptation plans at both the national and the regional levels in the National Climate Change Adaptation Strategy for 2035. (3) Strengthen China’s climate mitigation actions and ensure that health is included in China’s pathway to carbon neutrality. By promoting investments in zero-carbon technologies and reducing fossil fuel subsidies, the current rebounding trend in carbon emissions will be reversed and lead to a healthy, low-carbon future. (4) Increase awareness of the linkages between climate change and health at all levels. Health professionals, the academic community, and traditional and new media should raise the awareness of the public and policymakers on the important linkages between climate change and health.</p
The 2021 China report of the Lancet Countdown on health and climate change:Seizing the window of opportunity
The 2023 China report of the Lancet Countdown on health and climate change: taking stock for a thriving future
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