KBGAN: Adversarial Learning for Knowledge Graph Embeddings

We introduce KBGAN, an adversarial learning framework to improve the performances of a wide range of existing knowledge graph embedding models. Because knowledge graphs typically only contain positive facts, sampling useful negative training examples is a non-trivial task. Replacing the head or tail entity of a fact with a uniformly randomly selected entity is a conventional method for generating negative facts, but the majority of the generated negative facts can be easily discriminated from positive facts, and will contribute little towards the training. Inspired by generative adversarial networks (GANs), we use one knowledge graph embedding model as a negative sample generator to assist the training of our desired model, which acts as the discriminator in GANs. This framework is independent of the concrete form of generator and discriminator, and therefore can utilize a wide variety of knowledge graph embedding models as its building blocks. In experiments, we adversarially train two translation-based models, TransE and TransD, each with assistance from one of the two probability-based models, DistMult and ComplEx. We evaluate the performances of KBGAN on the link prediction task, using three knowledge base completion datasets: FB15k-237, WN18 and WN18RR. Experimental results show that adversarial training substantially improves the performances of target embedding models under various settings.Comment: To appear at NAACL HLT 201

The JAK/STAT pathway positively regulates DPP signaling in the Drosophila germline stem cell niche

The stem cell niche, formed by surrounding stromal cells, provides extrinsic signals that maintain stem cell self-renewal. However, it remains unclear how these extrinsic signals are regulated. In the Drosophila female germline stem cell (GSC) niche, Decapentaplegic (DPP) is an important niche factor for GSC self-renewal. The exact source of the DPP and how its transcription is regulated in this niche remain unclear. We show that dpp is expressed in somatic cells of the niche including the cap cells, a subtype of niche cells. Furthermore, our data show that the Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway positively regulates dpp expression in the cap cells, suggesting that JAK/STAT activity is required in somatic niche cells to prevent precocious GSC differentiation. Our data suggest that the JAK/STAT pathway functions downstream/independently of cap cell formation induced by Notch signaling. JAK/STAT signaling may also regulate dpp expression in the male GSC niche, suggesting a common origin of female and male GSC niches

Use of the Fixed Point Theorem to Mine Data from a Knowledge-base

"One gram ofknowledge is worth of tons of gold". The desire to obtain knowledge from collected data has generated a need for new techniques and tools that can transform the processed data into useful information and knowledge intelligently and automatically. Consequently, data mining has become a research area with increasing importance. Data mining, which is also known as knowledge discovery in databases, is the process of extracting and refining implicit, previously unknown and potentially useful knowledge from databases. Much research has set mining information and knowledge from databases as a key research topic. It also becomes an important area with major revenues opportunity for companies. Many researchers in the area of database systems, data warehousing, statistics, artificial intelligence, and expert systems have shown their interest in data mining. In response to such a demand a new data mining technique, the use of the perfect fixed point theorem is discussed and validated in this thesis. By using the perfect fixed point theorem in knowledge-bases, people can obtain some useful (previously unknown) information. It can help decision makers to make more accurate predications. Also, it can save time and money for decision makers and the researchers in other scientific and technology fields

Subsurface multiphase reactive flow in geologic CO2 storage: Key impact factors and characterization approaches

Multiple measurements and data sets show unequivocally that levels of carbon dioxide (CO2) have been increasing in the Earth's atmosphere for the past several centuries, with the rate becoming  steeper in recent decades (Soeder, 2021). Carbon capture, utilization and storage (CCUS) has been regarded as an effective approach to swiftly cut CO2 emissions. Among the existing CCUS technologies, CO2 geological utilization and storage has the highest technological maturity, and is the most vital “sink” to consume the captured CO2. For CO2 geological utilization and storage, large amounts of CO2 need to be injected into the deep subsurface, and the CO2 flow in the subsurface is a very complicated process. The flow system is a two-phase or even a three-phase system, and flow in pores needs to be clearly distinguished from flow in fractures and wellbores. Most importantly, wettability, pore structure, geochemical reactions play very important roles in governing subsurface CO2 flow. Without a clear understanding of how the impact factors affect CO2 flow, it is difficult to predict the CO2 impairs the confidence of policy makers and investors to support large-scale geologic CO2 storage. To study CO2 flow, there is a need to develop effective approaches to characterize CO2 flow in subsurface system. This work discusses several key factors that have strong impact on subsurface CO2 flow, and an effective approach for CO2 flow characterization. Impact of wettability and pore structure on multiphase flow. The injection of CO2 into geological formations displaces brine from pore spaces, resulting in various CO2-brine displacement patterns, such as capillary fingering, viscous fingering, crossover, and compact displacement. These patterns also occur as the brine later flows back to displace supercritical CO2 when the injection stops. The CO2-brine displacement results in CO2 becoming trapped as droplets and ganglia in pore spaces, referred to as residual trapping or capillary trapping. Wettability and pore structure have significant effects on CO2-brine displacement patterns and capillary trapping. The wettability represents the affinity of fluid to the solid surface. By changing the capillary force governed by the Young-Laplace law, the wettability modifies the local porefilling events and thus impacts the displacement patterns. Increasing the wettability of the invading fluid from drainage to imbibition stabilizes the displacement front due to the cooperative pore-filling events at the pore scale (Holtzman and Segre, 2015). However, the displacement pattern will change extensively as a result of corner flow when the invading fluid is strongly wetting to the solid surface (Hu et al., 2018). On the other hand, the role of pore structure in displacement patterns may depend on the type of permeable media. The pore-scale disorder, which represents the randomness of pore size, changes the threshold capillary pressure and affects the local pore-filling paths. Increasing disorder promotes unstable displacement patterns for both drainage and imbibition conditions (Toussaint et al., 2005), but under certain wettability conditions, higher disorder may enhance cooperative porefilling events and thus smooth the displacement front. The roughness variations in the aperture between the two rough surfaces determines the flow path and controls the displacement patterns for a fractured medium. Therefore, the transition of CO2-brine displacement patterns under various wetting and pore structure conditions is an open challenge and a very active area of research.Impact of geochemical reactions on multiphase flow. Geochemical reactions play a key role in determining CO2 flow patterns. Though geochemical reaction-induced mineral trapping can only become vital after hundreds to thousands years of CO2 injection in reservoir scale, fast mineral dissolution and precipitation in micro-scale flow channels of host rocks and caprocks can change permeability of the rocks and thus influence the migration behaviour of injected CO2 (Zhang et al., 2019). For carbonate rocks, CO2 injection usually causes opening of flow channels due to dissolution of carbonates, which enhances CO2 injectivity and is beneficial for largescale CO2 storage (Yang et al., 2020). A sandstone reservoir that contains large amounts of feldspars and glauconite may have a strong CO2-sandstone interaction, which usually causes sealing of flow channels due to precipitation of secondary minerals (Xu et al., 2004). However, given different types of flow channels and varying reaction environments, it is very difficult to precisely predict if a given flow channel in a rock will open or close under the influence of geochemical reactions. Therefore, an important research direction in the future is to find out a criterion that can determine if a flow  channel will open or close under the influence of geochemical reactions, with the consideration of complicated reaction environments.Pore-scale modeling of multiphase reactive flow. Compared with continuum-scale models, pore-scale modeling, which directly reflects the realistic porous structures, provides a powerful tool for studying the multiphase flow, species transport, chemical reaction and mineral dissolution/precipitation processes (Chen et al., 2022). Effects of pressure, temperature, fluid properties, wettability, pore size and porous morphology on the supercritical CO2-water two-phase flow and distributions have been extensively studied by pore-scale modeling. Pore-scale modeling that reveals the mechanisms of nonequilibrium supercritical CO2 dissolution into the surrounding brine will be beneficial for enhancing CO2 solubility trapping. Recently, supercritical CO2 storage in the depleted oil reservoir has also drawn increasing attention, and the resulting supercritical CO2-oil-water three-phase flow are extremely complicated (Zhu et al., 2021). Pore-scale modeling is an ideal tool to study the effects of structure heterogeneity, mineral composition and reaction kinetics on the rock dissolution processes. Further pore-scale modeling work to investigate the effects of  twophase or three-phase flow on mineral dissolution/precipitation processes are helpful for better understanding the CO2 storage processes in saline formations or depleted oil reservoirs. AcknowledgementThis work was performed by the support of Key R&D Program of Inner Mongolia Province of China (No. 2021ZD0034-3) and the National Natural Science Foundation of China (Nos. 42172315, 42141011 and 52122905).Cited as: Zhang, L., Chen, L., Hu, R., Cai, J. Subsurface multiphase reactive flow in geologic CO2 storage: Key impact factors and characterization approaches. Advances in Geo-Energy Research, 2022, 6(3): 179-180. https://doi.org/10.46690/ager.2022.03.0

Dynein-mediated apical localization of crumbs transcripts is required for Crumbs activity in epithelial polarity

Asymmetrical localization of transcripts coupled with localized translation constitutes an important mechanism widely deployed to regulate gene activity in a spatial manner. The conserved transmembrane protein Crumbs (Crb) is an important regulator of epithelial polarity. However, it remains unclear how Crb is targeted to the apical domain. Here, we show that the cytoplasmic dynein complex transports both Crb protein and transcripts to the apical domain of Drosophila melanogaster follicular cells (FCs). The crb 3′ untranslated region (UTR) is necessary and sufficient for the apical localization of its transcript and this apical transcript localization is crucial for crb function. In crb mutant FCs, Crb protein derived from transgenes lacking the 3′ UTR does not effectively localize to the apical domain and does not effectively restore normal epithelial polarity. We propose that dynein-mediated messenger RNA transport coupled with a localized translation mechanism is involved in localizing Crb to the apical domain to mediate epithelial apicobasal polarity and that this mechanism might be widely used to regulate cellular polarity