Wettability Alteration of Sandstone by Chemical Treatments

Liquid condensation in the reservoir near a wellbore may kill gas production in gas-condensate reservoirs when pressure drops lower than the dew point. It is clear from investigations reported in the literature that gas production could be improved by altering the rock wettability from liquid-wetness to gas-wetness. In this paper, three different fluorosurfactants FG1105, FC911, and FG40 were evaluated for altering the wettability of sandstone rocks from liquid-wetting to gas-wetting using contact angle measurement. The results showed that FG40 provided the best wettability alteration effect with a concentration of 0.3% and FC911 at the concentration of 0.3%

ProtoEM: A Prototype-Enhanced Matching Framework for Event Relation Extraction

Event Relation Extraction (ERE) aims to extract multiple kinds of relations among events in texts. However, existing methods singly categorize event relations as different classes, which are inadequately capturing the intrinsic semantics of these relations. To comprehensively understand their intrinsic semantics, in this paper, we obtain prototype representations for each type of event relation and propose a Prototype-Enhanced Matching (ProtoEM) framework for the joint extraction of multiple kinds of event relations. Specifically, ProtoEM extracts event relations in a two-step manner, i.e., prototype representing and prototype matching. In the first step, to capture the connotations of different event relations, ProtoEM utilizes examples to represent the prototypes corresponding to these relations. Subsequently, to capture the interdependence among event relations, it constructs a dependency graph for the prototypes corresponding to these relations and utilized a Graph Neural Network (GNN)-based module for modeling. In the second step, it obtains the representations of new event pairs and calculates their similarity with those prototypes obtained in the first step to evaluate which types of event relations they belong to. Experimental results on the MAVEN-ERE dataset demonstrate that the proposed ProtoEM framework can effectively represent the prototypes of event relations and further obtain a significant improvement over baseline models.Comment: Work in progres

An In-Context Schema Understanding Method for Knowledge Base Question Answering

The Knowledge Base Question Answering (KBQA) task aims to answer natural language questions based on a given knowledge base. As a kind of common method for this task, semantic parsing-based ones first convert natural language questions to logical forms (e.g., SPARQL queries) and then execute them on knowledge bases to get answers. Recently, Large Language Models (LLMs) have shown strong abilities in language understanding and may be adopted as semantic parsers in such kinds of methods. However, in doing so, a great challenge for LLMs is to understand the schema of knowledge bases. Therefore, in this paper, we propose an In-Context Schema Understanding (ICSU) method for facilitating LLMs to be used as a semantic parser in KBQA. Specifically, ICSU adopts the In-context Learning mechanism to instruct LLMs to generate SPARQL queries with examples. In order to retrieve appropriate examples from annotated question-query pairs, which contain comprehensive schema information related to questions, ICSU explores four different retrieval strategies. Experimental results on the largest KBQA benchmark, KQA Pro, show that ICSU with all these strategies outperforms that with a random retrieval strategy significantly (from 12\% to 78.76\% in accuracy)

Robust Adaptive Depth Control of Hybrid Underwater Glider in Vertical Plane

Hybrid underwater glider (HUG) is an advanced autonomous underwater vehicle with propellers capable of sustainable operations for many months. Under the underwater disturbances and parameter uncertainties, it is difficult that the HUG coordinates with the desired depth in a robust manner. In this study, a robust adaptive control algorithm for the HUG is proposed. In the descend and ascend periods, the pitch control is designed using backstepping technique and direct adaptive control. When the vehicle approaches the target depth, the surge speed control using adaptive control combined with the pitch control is used to keep the vehicle at the desired depth with a constant cruising speed in the presence of the disturbances. The stability of the proposed controller is verified by using the Lyapunov theorem. Finally, the computer simulation using the numerical method is conducted to show the effectiveness of the proposed controller for a hybrid underwater glider system

Nested Event Extraction upon Pivot Element Recogniton

Nested Event Extraction (NEE) aims to extract complex event structures where an event contains other events as its arguments recursively. Nested events involve a kind of Pivot Elements (PEs) that simultaneously act as arguments of outer events and as triggers of inner events, and thus connect them into nested structures. This special characteristic of PEs brings challenges to existing NEE methods, as they cannot well cope with the dual identities of PEs. Therefore, this paper proposes a new model, called PerNee, which extracts nested events mainly based on recognizing PEs. Specifically, PerNee first recognizes the triggers of both inner and outer events and further recognizes the PEs via classifying the relation type between trigger pairs. In order to obtain better representations of triggers and arguments to further improve NEE performance, it incorporates the information of both event types and argument roles into PerNee through prompt learning. Since existing NEE datasets (e.g., Genia11) are limited to specific domains and contain a narrow range of event types with nested structures, we systematically categorize nested events in generic domain and construct a new NEE dataset, namely ACE2005-Nest. Experimental results demonstrate that PerNee consistently achieves state-of-the-art performance on ACE2005-Nest, Genia11 and Genia13

A riboflavin transporter deficiency presenting as pure red cell aplasia: a pediatric case report

IntroductionRiboflavin transporter deficiency (RTD) is a rare genetic disorder that affects riboflavin transport, leading to impaired red blood cell production and resulting in pure red cell aplasia. Recognizing and understanding its clinical manifestations, diagnosis, and management is important.Case presentationA 2-year-old patient presented with pure red cell aplasia as the primary symptom of RTD. After confirming the diagnosis, rapid reversal of anemia was achieved after high-dose riboflavin treatment.ConclusionRTD often has an insidious onset, and neurological symptoms appear gradually as the disease progresses, making it prone to misdiagnosis. Genetic testing and bone marrow biopsy can confirm the diagnosis

KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction

In this paper, we propose KnowCoder, a Large Language Model (LLM) to conduct Universal Information Extraction (UIE) via code generation. KnowCoder aims to develop a kind of unified schema representation that LLMs can easily understand and an effective learning framework that encourages LLMs to follow schemas and extract structured knowledge accurately. To achieve these, KnowCoder introduces a code-style schema representation method to uniformly transform different schemas into Python classes, with which complex schema information, such as constraints among tasks in UIE, can be captured in an LLM-friendly manner. We further construct a code-style schema library covering over $\textbf{30,000}$ types of knowledge, which is the largest one for UIE, to the best of our knowledge. To ease the learning process of LLMs, KnowCoder contains a two-phase learning framework that enhances its schema understanding ability via code pretraining and its schema following ability via instruction tuning. After code pretraining on around $1.5$B automatically constructed data, KnowCoder already attains remarkable generalization ability and achieves relative improvements by \textbf{49.8%} F1, compared to LLaMA2, under the few-shot setting. After instruction tuning, KnowCoder further exhibits strong generalization ability on unseen schemas and achieves up to \textbf{12.5%} and \textbf{21.9%}, compared to sota baselines, under the zero-shot setting and the low resource setting, respectively. Additionally, based on our unified schema representations, various human-annotated datasets can simultaneously be utilized to refine KnowCoder, which achieves significant improvements up to \textbf{7.5%} under the supervised setting

Benzyl isothiocyanate induces apoptosis and inhibits tumor growth in canine mammary carcinoma via down-regulation of the cyclin B1/Cdk1 pathway

Background: Canine mammary carcinoma is common in female dogs, and its poor prognosis remains a serious clinical challenge, especially in developing countries. Benzyl isothiocyanate (BITC) has attracted great interest because of its inhibitory effect against tumor activity. However, its effect and the underlying mechanisms of action in canine mammary cancer are not well-understood. Here, we show that BITC suppresses mammary tumor growth, both in vivo and in vitro, and reveal some of the potential mechanisms involved. Methods: The effect of BITC on canine mammary cancer was evaluated on CIPp and CMT-7364, canine mammary carcinoma lines. The cell lines were treated with BITC and then subjected to wound healing and invasion assays. Cell cycles and apoptosis were measured using flow cytometry; TUNEL assay; immunohistochemistry (IHC) for caspase 3, caspase 9, and cyclin D1; hematoxylin and eosin (H&E) staining; and/or quantitative polymerase chain reaction (qPCR). Results: BITC showed a strong suppressive effect in both CIPp and CMT-7364 cells by inhibiting cell growth in vitro; these effects were both dose- and time-dependent. BITC also inhibited migration and invasion of CIPp and CMT-7364 cells. BITC induced G2 arrest and apoptosis, decreasing tumor growth in nude mice by downregulation of cyclin B1 and Cdk1 expression. Conclusion: BITC suppressed both invasion and migration of CIPp and CMT-7364 cells and induced apoptosis. BITC inhibited canine mammary tumor growth by suppressing cyclinB1 and Cdk1 expression in nude mice

towards scalable processing for a large-scale ride sharing service

Ride sharing is a promising way to realize a convenient, economic and low-carbon travel. After analyzing and refining the requirements of a ride sharing service, the paper models the trajectory matching therein and discusses the implementation of a large-scale ride sharing service with the aim of improving the efficiency and scalability.Kyushu Sangyo Univ (KSU), IEEE, IEEE Comp Soc, IEEE Tech Comm Scalable Comp (TCSC), Informat Proc Soc Japan (IPSJ), Inst Elect, Informat & Commun Engineers (IEICE), FCVB, IPSJ Special Interest Grp Distributed Proc Syst (IPSJ SIG-DPS), IEICE Special Interest Grp Dependable Comp (IEICE SIG-DC), IPSJ Special Interest Grp Comp Secur (IPSJ SIG-CSEC), IPSJ Special Interest Grp Mobile Comp & Ubiquitous Commun (IPSJ SIG-MBL)Ride sharing is a promising way to realize a convenient, economic and low-carbon travel. After analyzing and refining the requirements of a ride sharing service, the paper models the trajectory matching therein and discusses the implementation of a large-scale ride sharing service with the aim of improving the efficiency and scalability

On Physical Urban Boundaries, Urban Sprawl, and Compactness Measurement: A Case Study of the Wen-Tai Region, China

China’s rapid urbanization has been accompanied by serious urban sprawl. Instead of measuring the physical urban boundaries (PUBs), most of existing studies in China rely on yearbook statistics to describe the growth of urbanized area; therefore, the understanding of the actual form and quantity of urban sprawl are restrained. As the statistical unit is generally at or above the county level, these studies tend to omit the lower-level “larger towns”. This paper discusses the measurement of urban sprawl and compactness using multi-source data on the GIS platform through the case study of the Wen-Tai region in China. GlobeLand30 remote sensing image data, vector road network data, NPP/VIIRS nighttime light data, and points of interest (POIs) data are adopted. The new method enhances the identification of built-up areas in larger towns. Besides, the 2020s’ PUBs of this region, data for 2010 and 2000 are retraced to assess the urban expansion rate, and two approaches are used to discuss the urban growth pattern. Additionally, a compactness model is constructed from four dimensions, i.e., the compactness of external contour, accessibility of road network, land-use intensity, and functional diversity, by which a high-resolution visual analysis tool is created for the provincial government to monitor urban sprawl