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Entity alignment is a key step in knowledge fusion,which aims to discover entity pairs with corresponding relations between knowledge graphs.Knowledge fusion enables a more extensive and accurate services for further knowledge graph applications.However,the entity names and relations are used insufficiently by most of the state-of-the-art models of entity alignment.After obtaining the vector representation of the entity,generally the alignment relations among the entities are obtained through single iterative strategy or direct calculation,while ignoring some valuable information,so that the result of entity alignment is not ideal.In view of the above problems,a multi-information optimized entity alignment model based on graph neural network(MOGNN) is proposed.Firstly,the input of the model fuses word information and character information in the entity name,and the vector representation of relations is learnt through attention mechanism.After transmitting the information by utilizing relations,MOGNN corrects the initial entity alignment matrix based on the pre-alignment results of entities and relations,and finally employs the deferred acceptance algorithm to further correct the misaligned results.The proposed model is validated on three subsets of DBP15K,and compared with the baseline models.Compared with the baseline models,Hits@1 increases by 4.47%,0.82% and 0.46%,Hits@10 and MRR have also achieved impressive results,and the effectiveness of the model is further verifies by ablation experiments.Therefore,more accurate entity alignment results can be obtained with the proposed model.

To provide theoretical reference for owners to identify unbalanced bids, this paper aims to construct an identification method based on grey relational and fuzzy set theory. Firstly, to measure the closeness degree between bidding unit price from engineering's estimated price, grey relational analysis theory is used to express the relationship between them. Secondly, a combined weight method determining all line items is calculated through integrating analytic hierarchy model and maximizing deviation method. Thirdly, based on fuzzy set theory, the membership degree and the fuzzy relation matrix are constructed, and then a fuzzy comprehensive identification method is established to identify unbalanced bidding. Fourthly, on the basis of fuzzy comprehensive identification method, the scoring set and total score vector are designed, and the rank of unbalanced bids is obtained by total score vector. Finally, a practical construction project bidding is stated to illustrate the effectiveness and practicability of the proposed method. Key words: project management, unbalanced bid, identification, grey-fuzzy evaluation method. Afin de fournir une reference theorique aux proprietaries pour determiner les soumissions inegales, le present document vise a construire une methode d'identification basee sur la theorie grise rationnelle et la theorie des ensembles flous. Premierement, dans le but de mesurer le degre de proximite entre le prix unitaire de la soumission et le prix estimatif de l'ingenierie, on utilise la theorie grise de l'analyse rationnelle pour exprimer la relation entre les deux. Deuxiemement, une methode de ponderation combinee pour determiner tous les postes est calculee en integrant un modele de hierarchie analytique et la methode d'ecart superieur. Troisiemement, sur la base de la theorie des ensembles flous, le degre d'appartenance et la matrice des relations floues sont construits, puis une methode d'identification globale floue est etablie pour determiner les soumissions inegales. Quatriemement, sur la base de la methode d'identification complete floue, l'ensemble des cotes et le vecteur des cotes globales sont concus, et le rang des soumissions inegales est obtenu par le vecteur des cotes globales. Enfin, une soumission pratique pour un projet de construction est presentee pour illustrer l'efficacite et la faisabilite de la methode proposee. Mots-cles: gestion de projet, soumission inegale, identification, methode devaluation grise-floue., Introduction Competitive bidding is one of the most common approaches for owners to select contractors in the construction industry (Takano et al. 2018). In the unit price contract, the measurement [...]

The performance data of water environment treatment public–private partnership (PPP) projects have the characteristics of multiple data sources, diverse types, and difficulties in integration. Based on existing literature and the characteristics of water environment treatment projects, this study establishes a performance evaluation index system for water environment treatment PPP projects. To address the multitemporal performance data, the data similarity method is employed to integrate multiple time data, while an ordered weighted averaging (OWA) operator is used to integrate multiple spatial location data. For indicator weighting, the OWA operator and overweighted weighting method are applied to allocate weights. Lastly, the Dempster–Shafer (D-S) evidence theory is utilized to evaluate project performance and determine the level of project performance. This model is implemented in the Pingyu County water environment treatment PPP project, yielding an overall performance level of level II (better). Additionally, the model offers distinct performance levels for each indicator, with special purpose vehicle (SPV) company governance B1 , water conservancy facilities B3 , garden plants B6 , and bridges B7 all achieving level III (general). Future managers can concentrate on enhancing these indicators to improve project performance. The incorporation of this approach for integrating multiple spatiotemporal data in performance evaluation enhances the reliability of results and carries substantial practical implications for advancing the sustainable development of water environment governance PPP projects. [ABSTRACT FROM AUTHOR]

To scientifically evaluate the implementation of the River Chief System (RCS), accelerate the overall improvement of the water ecological environment, and promote the sustainable development of river and lake functions, this study selects 26 evaluation indicators from six aspects, including the effectiveness of organization and management, the effectiveness of water resources protection, the effectiveness of water environment management, the effectiveness of water pollution prevention and control, the effectiveness of water ecological restoration, and the effectiveness of the management of the waterside shoreline, and establishes an evaluation system for the effectiveness of the implementation of the RCS. Among the 26 indicators, data for the qualitative indicators mainly come from a series of statistical yearbooks and RCS reports, while data for the quantitative indicators are obtained through scoring by more than 20 experts and calculating the average. The CRITIC objective weighting method is improved from three aspects of comparison intensity, correlation coefficient, and degree of variation, and the subjective weighting of indicators is carried out using the AHP 1–5 scale method. The optimal linear combination of subjective and objective weighting results is obtained using the combination weighting method with game theory, which is auxiliary to the set pair analysis. Considering the "certainty" and "uncertainty" in the evaluation process, the four-element connection number model of set pair analysis is established to evaluate the implementation effect of the RCS in Henan Province from 2018 to 2021. The results show that the implementation effect of the RCS in Henan Province improves year by year and reaches excellent in 2019. The results of this study can be used as a reference for evaluating the work of the RCS in other regions and can also provide a reference for the study of evaluation problems in other fields. [ABSTRACT FROM AUTHOR]

The sustainability of financing is an important measure in the development of supply chains. However, the difficulty and high cost of financing have always been critical factors hindering the sustainable development of small and medium-sized enterprises (SMEs). Blockchain technology (BT) is an effective tool to relieve the current problem. Based on it, this study aims to establish Blockchain-driven incentives and restraint mechanisms for SME financing using a dynamic game model in which financial institutions (FIs) and new agricultural business entities (NABEs) are regarded as game subjects. By analyzing the impact of key parameters on the equilibrium state of the game for all stakeholders, several findings are drawn as follows. (1) The usage of BT affects FI loan strategies by influencing their cost in supply chain financing. (2) The usage of BT affects NABE's strategy choice by influencing their loan interest rate. (3) The usage of BT affects NABE's strategy choice by influencing their default losses. (4) The usage of BT affects NABE's and FI's strategy choices by influencing their additional benefits. This study provides decision-making support for optimal strategy decisions under different conditions and serves as a theoretical reference for the government in formulating financing incentive and restraint mechanisms. [ABSTRACT FROM AUTHOR]

Implementing the low-carbon transformation strategy has become an inevitable choice for manufacturing enterprises. However, suppliers often overlook the impact of consumers' preferences for low-carbon products (LCPs) on their own low-carbon strategies. Based on this idea, this study uses game theory models to analyze how consumer preferences affect suppliers' decision-making and coordination strategies in low-carbon supply chains (LCSCs). Results show that (1) manufacturers and retailers are more likely to produce and promote LCPs as consumers become more sensitive to carbon emission reduction (CER); (2) manufacturers are less likely to produce LCPs but retailers are more likely to promote them as consumers become more sensitive to promotional rates; and (3) manufacturers are less likely to produce LCPs but retailers are more likely to promote them as consumers become more sensitive to retail prices. This study concludes that consumer preferences play a crucial role in determining suppliers' decisions and coordination strategies in LCSCs. [ABSTRACT FROM AUTHOR]

In the public–private partnership (PPP) supply chain, trust serves as the foundation for collaboration between investment companies and suppliers. However, due to many uncertain factors, the evolution of trust remains a "black box" phenomenon. In order to analyze the impact of the evolution of trust in the PPP supply chain on investment companies and suppliers' strategic choices, and promote the healthy and sustainable development of PPP supply chain projects, this paper establishes a trust evolutionary game model, which analyzes the evolutionary paths under different scenarios and explores the impact of parameters on the cooperative strategies of participants. The findings indicate that trust asymmetry or an increase in trust can facilitate investment companies and suppliers to opt for positive cooperation strategies. Furthermore, both parties' strategies are less influenced by their initial willingness and more by trust degree. The moral risk coefficient and information asymmetry coefficient have a negative effect on the cooperative strategies, with the moral risk coefficient of investment companies exhibiting a more significant impact on the entire cooperation process. Moreover, both parties can only choose positive strategies when the information asymmetry coefficient is low. This study holds significant implications for promoting cooperation, enhancing contract performance, safeguarding the interests of all parties, and increasing cooperation satisfaction. [ABSTRACT FROM AUTHOR]

The onset of transition to cellularity and self-similar propagation of centrally ignited, expanding spherical flames in a reactive environment of H2/O2/N2 and H2/O2/He mixtures at initial pressures up to 15 bar were experimentally investigated using a newly developed, constant-pressure, dual-chamber vessel and were theoretically interpreted based on linear stability theory. The experiments were well-controlled to identify the separate and coupled effects of Darrieus–Landau instability and diffusional–thermal instability. Results show that the critical radius, rcr, for the onset of cellular instability varies non-monotonously with initial pressure for fuel-lean and stoichiometric H2/O2/N2 flames. This non-monotonous pressure dependence of rcr is well captured by linear stability theory for stoichiometric flames. The experimental critical Peclet number, Pecr = rcr/δf, increases non-linearly with the Markstein number, Ma, which measures the intensity of diffusional–thermal instability. However, a linear dependence of Pecr on Ma is predicted by linear stability theory. Specifically, the theory shows well quantitative agreement with the experimental results for mixtures with near-unity Leeff; however, it under-predicts the Pecr for mixtures with off-unity Leeff. In addition, there exists three distinct propagation stages for flames subjected to cellular instability, namely, smooth expansion, transition propagation, and self-similar propagation. The acceleration exponent, α, in the self-similar propagation stage was extracted based on the power-law of drf/dt = αA1/αrf(1 − 1/α), where rf is the instantaneous mean flame radius, and A is a constant. The values of α are located between 1.22 and 1.40, which are smaller than the suggested value (1.5) for self-turbulization. [ABSTRACT FROM AUTHOR]

A MCOHP (micro-channel oscillating heat pipe) can provide lightweight and efficient temperature control capabilities for aerospace spacecraft with a high power and small size. The research about the heat flow effects on the thermal performance of MCOHPs is both necessary and essential for aerospace heat dissipation. In this paper, the heat flow effects on the thermal performance of MCOHPs are summarized and studied. The flow thermal performance enhancement changes of MCOHPs are given, which are caused by the heat flow work fluids of nano-fluids, gases, single liquids, mixed liquids, surfactants, and self-humidifying fluids. The use of graphene nano-fluids as the heat flow work medium can reduce the thermal resistance by 83.6%, which can enhance the maximum thermal conductivity by 105%. The influences of gravity and flow characteristics are also discussed. The heat flow pattern changes with the work stage, which affects the flow mode and the heat and mass transfer efficiency of OHP. The effective thermal conductivity varies from 4.8 kW/(m·K) to 70 kW/(m·K) when different gases are selected as the working fluid in OHP. The study of heat flow effects on the thermal performance of MCOHPs is conducive to exploring in-depth aerospace applications. [ABSTRACT FROM AUTHOR]

Applying blockchain to supply chain financing is an effective way to solve the problems of financing difficulties, high financing costs, and slow financing for small and medium-sized enterprises (SMZEs). Using evolutionary game theory, this study constructs a tripartite game model and analyzes the influence of blockchain technology on the evolutionary stability strategies for financial institutions (FIs), core enterprises (CEs), and SMZEs, in which the default losses of CEs and SMZEs are assumed to be dynamic. The results of this study are as follows: (1) When CEs and SMZESs' default losses are lower than some critical value, they tend to break their promises. (2) When accounts receivable are greater than some critical value, CEs cannot repay on time because they can make a relatively large profits from delayed repayment, whereas SMZEs can be constrained to be trustworthy. Finally, the results using numerical simulation show that both relatively large default losses and enough large, trustworthy income sources can make CEs and SMZEs tend to keep their promises; in turn, CEs would be non-paying and the SMZEs tend to be trustworthy for relatively large accounts receivable. The results provide theoretical support for realizing healthy and sustainable development for supply chain finance. [ABSTRACT FROM AUTHOR]

Renal cyst development and expansion in autosomal dominant polycystic kidney disease (ADPKD) involves over‐proliferation of cyst‐lining epithelial cells and excessive cystic fluid secretion. While metformin effectively inhibits renal cyst growth in mouse models of ADPKD it exhibits low potency, and thus an adenosine monophosphate‐activated protein kinase (AMPK) activator with higher potency is required. Herein, we adopted a drug repurposing strategy to explore the potential of PF‐06409577, an AMPK activator for diabetic nephropathy, in cellular, ex vivo and in vivo models of ADPKD. Our results demonstrated that PF‐06409577 effectively down‐regulated mammalian target of rapamycin pathway‐mediated proliferation of cyst‐lining epithelial cells and reduced cystic fibrosis transmembrane conductance regulator‐regulated cystic fluid secretion. Overall, our data suggest that PF‐06409577 holds therapeutic potential for ADPKD treatment. [ABSTRACT FROM AUTHOR]

Due to the complexity and randomness of environmental change, the knowledge-sharing behavior of members in the PPP supply chain will be affected by random disturbance factors. Traditional evolutionary game models cannot describe this effect. In this study, Gaussian white noise is introduced into the stochastic evolutionary game model of PPP supply chain knowledge sharing. The numerical simulation of the model is carried out to analyze the influence of parameter changes on the strategy selection of enterprise groups. The result shows that the strong knowledge power enterprise group is more sensitive with the variation of parameters than that of the weak knowledge power enterprise group. However, the weak enterprise group has a more vital willingness to share knowledge. Incentive measures can increase the knowledge-sharing benefits and promote the strong knowledge powerful enterprise group toward the sharing strategy. Increasing the mutual trust coefficient, reducing the sharing cost, and improving the enterprise's transformation ability will help both sides to evolve into the sharing strategy more quickly. This study would have significance for PPP project performance and industry innovation. [ABSTRACT FROM AUTHOR]

Risk assessment of pollutants to humans and ecosystems requires much toxicological data. However, experimental testing of compounds expends a large number of animals and is criticized for ethical reasons. The in silico method is playing an important role in filling the data gap. In this paper, the acute toxicity data of 1221 chemicals to Vibrio fischeri were collected. The global models obtained showed that there was a poor relationship between the toxicity data and the descriptors calculated based on linear and nonlinear regression analysis. This is due to the fact that the studied compounds contain not only non-reactive compounds but also reactive and specifically acting compounds with different modes of action (MOAs). MOAs are fundamental for the development of mechanistically based QSAR models and toxicity prediction. To investigate MOAs and develop MOA-based prediction models, the compounds were classified into baseline, less inert, reactive, and specifically acting compounds based on the modified Verhaar's classification scheme. Satisfactory models were established by multivariate linear regression (MLR) and support vector machine (SVM) analysis not only for baseline and less inert chemicals, but also for reactive and specifically acting compounds. Compared with linear models obtained by the MLR method, the nonlinear models obtained by the SVM method had better performance. The cross validation proved that all of the models were robust except for those for reactive chemicals with nN (number of nitrogen atoms) = 0 and n(C=O) (number of carbonyl groups) > 0 (Q2ext < 0.5). The application domains and outliers are discussed for those MOA-based models. The models developed in this paper are significantly helpful not only because the application domains for baseline and less inert compounds have been expended, but also the toxicity of reactive and specifically acting compounds can be successfully predicted. This work will promote understanding of toxic mechanisms and toxicity prediction for the chemicals with structural diversity, especially for reactive and specifically acting compounds. [ABSTRACT FROM AUTHOR]

Wilms' tumour (WT) is a frequent primary malignant tumour of urinary system in children. LncRNAs small nucleolar RNA host gene 6 (SNHG6) modulates kinds of biological procedures of cancer cells. Our research is to explore the effect and associated regulatory mechanism of SNHG6 in WT. CCK8 assays and bromodeoxyuridine were used to determine cell viability and cell proliferation, respectively. Flow cytometric analysis was performed to measure cell apoptosis rate. Cell mobility was tested through transwell and migration assays. Western blotting was employed to test the expression of proteins related to cell proliferation, cell apoptosis and signal pathways. In the results, overexpression of SNHG6 was found in WT tissues. The knockdown of SNHG6 suppressed cell proliferation, migration and incursion, but promoted apoptosis. Further study found that the knockdown of SNHG6 elevated the expression of miR-15a. Then, the combination of miR-15a inhibitor abolished the inhibiting effect of si-SNHG6 on WT progression. We also found that the TAK1/JNK and Wnt/β-catenin signal pathways were inactivated by the knockdown of SNHG6 through elevating the expression of miR-15a. In summary, SNHG6 is an oncogene of WT development by targeting miR-15a. [ABSTRACT FROM AUTHOR]

Pythagorean fuzzy sets (PFSs), as an extension of intuitionistic fuzzy sets (IFSs) for dealing with uncertainty information, have attracted considerable attention in the decision-making area. The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is one of the most popular decision-making approaches. In the TOPSIS method, the desired alternative should have not only the shortest distance from the positive ideal solution, but also the farthest distance from the negative ideal solution. Similarity measures play an important role in assessing the degree between ideal and proposal alternatives in decision-making. Thus, this paper aims to provide an extended TOPSIS by developing new similarity measures with PFSs and applying it to multi-criteria decision-making (MCDM) problems. The main contributions of this paper are as follows: (1) development of three new similarity measures with PFSs, and investigation of their properties; (2) extension of the TOPSIS method based on the proposed similarity measures; and (3) establishment of a Pythagorean fuzzy decision-making method using the improved TOPSIS method. A case study on the selection of a project delivery system is conducted to show the applicability of the presented approach. [ABSTRACT FROM AUTHOR]

The rapid development of the economy in China resulted in increasingly serious water pollution problem. A lot of water pollution treatment projects have been launched to improve the water environment quality. Water pollution treatment is a complex and long-term task. Considering the concept of water pollution with fuzziness and the factors affecting the effect of water pollution treatment (EWPT), this study constructs a multi-dimensional dynamic fuzzy comprehensive monitoring model. The model considers the vague boundaries in the representation of water pollution and various factors affecting the treatment effect, such as monitoring time, monitoring index, and monitoring location. In detail, firstly, existing methods for evaluating the EWPT are analyzed and reviewed. Then a multi-dimensional dynamic model is developed for monitoring the EWPT. Finally, the Yueya Lake of Henan Province in China is taken as an example to demonstrate the effectiveness and practicability of the proposed method. From the analysis of the results, to maintain the cleanliness of the water, efforts should still be made to eliminate and completely block the pollutants on the shore in order to fundamentally solve the problem. [ABSTRACT FROM AUTHOR]

Background/Aims: A sodium-glucose co-transporter-2 inhibitor dapagliflozin is widely used for lowering blood glucose and its usage is limited in type 2 diabetes mellitus patients with moderate renal impairment. As its effect on kidney function is discrepant and complicated, the aim of this study is to determine the effect of dapagliflozin on the progression of diabetic nephropathy and related mechanisms. Methods: Twelve-week-old male C57BL/6 wild-type and db/db mice were treated with vehicle or 1 mg/kg dapagliflozin for 12 weeks. Body weight, blood glucose, insulin tolerance, glucose tolerance, pyruvate tolerance and 24-hour urine were measured every 4 weeks. At 24 weeks of age, renal function was evaluated by blood urea nitrogen level, creatinine clearance, urine output, urinary albumin excretion, Periodic Acid-Schiff staining, Masson’s trichrome staining and electron microscopy. Changes in insulin signaling and gluconeogenic key regulatory enzymes were detected using Western blot analysis. Results: Dapagliflozin did not alleviate but instead aggravated diabetic nephropathy manifesting as increased levels of microalbuminuria, blood urea nitrogen, and glomerular and tubular damage in db/db mice. Despite adequate glycemic control by dapagliflozin, urinary glucose excretion increased after administration before 24 weeks of age and was likely associated with renal impairment. Increased urinary glucose excretion was mainly derived from the disturbance of glucose homeostasis with elevated hepatic and renal gluconeogenesis induced by dapagliflozin. Although it had no effect on insulin sensitivity and glucose tolerance, dapagliflozin further induced the expression of gluconeogenic key rate-limiting enzymes through increasing the expression levels of FoxO1 in the kidney and liver. Conclusion: These experimental results indicate that dapagliflozin aggravates diabetes mellitus-induced kidney injury, mostly through increasing gluconeogenesis. [ABSTRACT FROM AUTHOR]

Background: The cAMP-PKA signaling pathway and TGF-ßl-dependent fibrosis pathways areof particular importance in ADPKD progression, but the cross-talk between these pathwaysremains unclear. Therefore, we used an MDCK-cell model and embryonic kidney-cyst modelto study the régulât ory role of cAMP-PKA signaling in the TGF-ßl induced fibrotic process. Method and Results: Pkd1flox/flox; Ksp-Cre and Pkd1+/+; Ksp-Cre mice were used as an in vivomodel. Increased kidney volume, renal cysts formation and up-regulation ofthefibrosis-relatedproteins TGF-βl, connective tissue growth factor (CTGF), and fibronectin (FN) can be observedin Pkd1flox/flox; Ksp-Cre mice. In an embryonic kidneys-cyst model, TGF-βll, FN and collagentype I were highly expressed. Western blotting revealed the obviously up-regulation of TGF-βl,CTGF, FN and collagen type I expression following forskolin treatment in MDCK cells. SelectivePKA inhibition with H89 may partially reversed the above effects. Pretreatment with the TGF-βRI kinase inhibitor VI SB431542 suppressed the increased expression of CTGF, FN and collagentype I caused by forskolin. Our data also indicate that forskolin inhibited TGF-β-inducedERK1/2 phosphorylation and FN up-regulation. ERK inhibition useing PD98059 significantlyinhibited the expression of CTGF, FN and collagen type I caused by TGF-βl. Conclusions: ThecAMP-PKA signaling pathway can directly promote the production of TGF-βl and/or TGFβl-dependent fibrogenetic molecules in MDCK cells and embryonic kidney cysts, but whenTGF-βl and its downstream pathways were highly expressed in MDCK cells, cAMP-PKA had asignificantly negative effect on TGF-βl induced p-ERKl/2 and FN expression. [ABSTRACT FROM AUTHOR]

In this study a series of polyimide (PI) films were synthesized from fluorinated and nonfluorinated monomers which contained diamines and dianhydrides. The influence of fluorine-containing groups on the glass transition temperature (T g) and tribological properties of the PI films was investigated. The wear mechanism for the different kinds of PI polymers was comparatively discussed. T g was characterized by dynamic mechanical analysis and the tribological changes were evaluated by friction and wear tests as well as scanning electron microscopy (SEM) analysis of the worn surfaces. Fourier transform infrared (FTIR) has been used to study the structures of the PI polymers. Experimental results indicated that the fluorine groups influenced the thermal behavior (T g) of the PI films. Nonfluorinated PI films have lower friction coefficient and wear rate compared with the fluorinated ones. It was also found that the tribological properties of the PI films were closely related with the applied load. The friction coefficients and wear rates reduced with increasing the applied load. [ABSTRACT FROM AUTHOR]