Multi-task Neural Network for Non-discrete Attribute Prediction in Knowledge Graphs

Many popular knowledge graphs such as Freebase, YAGO or DBPedia maintain a list of non-discrete attributes for each entity. Intuitively, these attributes such as height, price or population count are able to richly characterize entities in knowledge graphs. This additional source of information may help to alleviate the inherent sparsity and incompleteness problem that are prevalent in knowledge graphs. Unfortunately, many state-of-the-art relational learning models ignore this information due to the challenging nature of dealing with non-discrete data types in the inherently binary-natured knowledge graphs. In this paper, we propose a novel multi-task neural network approach for both encoding and prediction of non-discrete attribute information in a relational setting. Specifically, we train a neural network for triplet prediction along with a separate network for attribute value regression. Via multi-task learning, we are able to learn representations of entities, relations and attributes that encode information about both tasks. Moreover, such attributes are not only central to many predictive tasks as an information source but also as a prediction target. Therefore, models that are able to encode, incorporate and predict such information in a relational learning context are highly attractive as well. We show that our approach outperforms many state-of-the-art methods for the tasks of relational triplet classification and attribute value prediction.Comment: Accepted at CIKM 201

Impact of Enteromorpha Blooms on Aquaculture Research Off Qianliyan Island, Yellow Sea, China

Between 2008 and 2016, there were mass summer blooms of Enteromorpha in the Yellow Sea, China. They covered an area of thousands of square kilometers annually, lasting an average of 90 days. Remote sensing data, model predictions, and marine environment ecological data measured by ships before, during, and after the Enteromorpha blooms were used in this study of the Qianliyan Island area. Underwater robots survey trepang, wrinkles abalone, and submarine ecological status. We found that the time taken by Enteromorpha to cover the Qianliyan Island area was relevant, as were changes in sea surface temperature (SST). The Enteromorpha made a rise in inorganic nitrogen, reactive phosphate, and heavy metals content in upper, middle, and bottom layers of sea water, dissolved oxygen (DO) and pH were reduced; and there were changes in the dominant animal and plant population. Enteromorpha sedimentation during outbreaks was measured by benthos sampling. Considerable growth in starfish number was obtained by underwater robot observation. All of this directly influenced the regional ecological environment. Numbers of trepang and wrinkles abalone were declined over the years. Global warming and SST anomalies are the two main reasons for frequent marine disasters that take place. National aquatic germ plasm resources of Qianliyan should be protected from the blooms

Anatomical Invariance Modeling and Semantic Alignment for Self-supervised Learning in 3D Medical Image Analysis

Self-supervised learning (SSL) has recently achieved promising performance for 3D medical image analysis tasks. Most current methods follow existing SSL paradigm originally designed for photographic or natural images, which cannot explicitly and thoroughly exploit the intrinsic similar anatomical structures across varying medical images. This may in fact degrade the quality of learned deep representations by maximizing the similarity among features containing spatial misalignment information and different anatomical semantics. In this work, we propose a new self-supervised learning framework, namely Alice, that explicitly fulfills Anatomical invariance modeling and semantic alignment via elaborately combining discriminative and generative objectives. Alice introduces a new contrastive learning strategy which encourages the similarity between views that are diversely mined but with consistent high-level semantics, in order to learn invariant anatomical features. Moreover, we design a conditional anatomical feature alignment module to complement corrupted embeddings with globally matched semantics and inter-patch topology information, conditioned by the distribution of local image content, which permits to create better contrastive pairs. Our extensive quantitative experiments on three 3D medical image analysis tasks demonstrate and validate the performance superiority of Alice, surpassing the previous best SSL counterpart methods and showing promising ability for united representation learning. Codes are available at https://github.com/alibaba-damo-academy/alice.Comment: This paper has been accepted by ICCV 2023 (oral

Effect of hydrogen sulfide on PC12 cell injury induced by high ATP concentration

Purpose: To investigate the potential protective effect of hydrogen sulfide against neural cell damage induced by a high-concentration of adenosine triphosphate (ATP).Methods: PC12 cells were incubated with ATP in order to induce cell damage. The extracellular level of H2S and protein expression of cystathionine-β-synthase (CBS) were determined. The PC12 cells pretreated with NaHS, aminooxyacetic acid (AOAA) and KN-62, prior to further incubation with ATP, and the effect of the treatments on cell viability was investigated.Results: High-concentration ATP induced cell death in PC12 cells, and this was accompanied by markedly increased contents of extracellular H2S and CBS expression (p < 0.05). The ATP-induced cytotoxicity was significantly compromised after pretreatment with H2S. (p < 0.05). The viability of PC12 cells pretreated with NaHS and AOAA was significantly higher than that of PC12 cells treated with ATP alone. In addition, the viability of ATP-treated PC12 cells was further markedly increased after pretreatment with NaHS and KN-62 (p < 0.05).Conclusion: ATP induced a concentration- and time-dependent cytotoxicity in PC12 cells via theendogenous H2S/CBS system. Supplementation with exogenous H2S mitigated the cell damageinduced by high concentration of ATP via a specific mechanism which may be specifically related to P2X7R

The effect of Matmo typhoon on mixed zone between the Yellow sea and Bohai sea

The results of remote sensing, buoy and profile based on measured data indicate that the wind speed, H-1/3 and salinity increased, sea surface temperature declined, and wind direction changed greatly during the transit of the Matmo typhoon on July 25. It was found that the typhoon transport the Yellow Sea Cold Water Mass into the the Yellow and Bohai seas mixed zone

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Research of the influencing factors of the immobilized redox mediators accelerating Cr(Ⅵ) reduction by Escherichia coli BL21

In order to study the influencing factors of non-dissolved redox mediators on Cr (Ⅵ) bioreduction, the accelerating effect of non-dissolved redox mediators immobilized by cellulose acetate (CA) on the reduction of Cr(Ⅵ) by Escherichia coli BL21 is investigated. The results show that the accelerating order is 1-chloroanthraquinone>1,5-dichloroanthraquinone>2-chloroanthraquinone>1,8-dichloroanthraquinone>anthraquinone>1,4,5,8-tetrachloroanthtaquinone; the optimal concentration of 1-chloroanthraquinone pH and initial Cr(Ⅵ) concentration are 0.048 mol/L, 7.00 and 30 mg/L, respectively; the removal rate increases with the increasing temperature when it is in the range of 20~60 ℃; after 6 times of recycling experiments, and the Cr(Ⅵ) bioreduction rate with the immobilized 1-chloroanthraquinone maintains above 5 times of margin bacterium's. It indicates that non-dissolved redox mediators immobilized by CA can effectively accelerate the reduction rate of Cr(Ⅵ) by Escherichia coli BL21, which has favourable application value

Effect of different ratios of cow manure and corn straw on the mixed anaerobic fermentation rate

In order to study the effect of the different ratios on the anaerobic fermentation rate is investigated, and the rate-limiting factors are preliminarily determined, at mesophilic (38±1)℃ condition, with anaerobic granular sludge as inoculums, different ratios of cow manure and corn straw are used as substrate for mixed anaerobic fermentation. By measuring daily biogas production, the concentrations of CH4 and CO2 in the marsh gas, TC, the concentration of VFAs and pH value, The results show that under the mixture ratio of 2∶1, the hydrolysis rate constants, cumulative biogas yield and biodegradability CH4 reach their high limits, which are 0.043 7 d<sup>-1</sup>, 271.93 mL/g and 71.59%, respectively. Moreover, it is found that the concentration of acetic acid is proportional to the amount of cow manure at the beginning (the first day) of mixed fermentation, and the concentration of propionicacid is proportional to the amount of corn straw in medium fermentation stage (the fifth day). In addition, rate-limiting step of biogas production is related to the ratio of cow manure and corn in fermentation material. With the increasing of corn straw proportion, on the 1st day, it tends to hydrolysis acidogenesis; from the 2th day to 15th day, it tends to hydrogen-production acetogenisis; and from the 16th day to 30th day, it is hydrolysis acidogenesis. The paper focuses on the relationship between the ratio of cow manure and corn straw and the rate-limiting step for biogas production, which could provide a theoretical and experimental support for improving the efficiency of biogas production in mixed fermentation