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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]

Purpose: The optimal payment in the whole operation and maintenance period of water environment treatment PPP projects has become the main approach to realize sustainable development of projects. This study is aimed at constructing an effective payment model for the whole life period of projects to achieve win-win among all stakeholders, so as to provide a theoretical reference and managerial implications for the public sector in the whole operation and maintenance period. Design/methodology/approach: In the whole operation and maintenance period of water environment treatment PPP projects, this article investigates how the public sector optimizes the payment in the whole operation and maintenance period of projects. Firstly, the projects' whole operation and maintenance period is divided into several stages according to the performance appraisal period. And then, the multi-stage dynamic programming model is constructed to design the payment construct model for the public sector in each performance appraisal stage. The payment from the public sector is the decision variable, and the deduction from the private sector is a random variable. Findings: The optimal payment model showed that the relatively less objective weight of public sector leaded to its relatively more total payment and vice versa. Therefore, the sustainable development of the projects can only be ensured when the objective weights both of them should be balanced. Additionally, the deduction from the performance appraisal of private sector plays an important role in the model construction. The larger deduction the private sector undertakes, the smaller profits private sector has. Since the deduction at each stage is a random variable, the deduction varies with the different probability distributions obeyed by the practical deduction in each stage. Research limitations/implications: The findings from this study have provided theoretical and application references, and some managerial implications are also given. First, the improvement of the pricing system of public sector should be accelerated. Second, the reasonable profit of the private sector must be guaranteed. While pursuing the maximization of social benefits, the public sector should make full use of the price sharing mechanism in the market and supervise the real income situation of the private sector. Third is increasing the public to participate in pricing. Additionally, it is a limitation that the deduction is assumed to conform to a uniform distribution in this study. Other probability distributions on deduction can be essentially further sought, so as to be more line with the actual situation of the projects. Originality/value: The optimal payment in whole operation and maintenance period of the projects has become an important issue, which is a key to project success. This study constructs a multi-stage dynamic programming model to optimize payment in the whole period of projects. Additionally, this study adds its value through deeply developing the new theories of optimal payment to more suitable for the practical problems, so that to optimize the design of payment mechanism. Meanwhile, a valuable reference for public and private sectors is provided to ensure the sustainable development of the 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]

For the first time, a global regression quantitative structure–toxicity/activity relationship (QSTR/QSAR) model was developed for the toxicity of a large data set including 1236 chemicals towards Vibrio fischeri, by using random forest (RF) regression algorithm. The optimal RF model with RF parameters of mtry = 3, ntree = 150 and nodesize = 5 was based on 13 molecular descriptors. It can achieve accurate prediction for the toxicity of 99.1% of 1236 chemicals, and yield coefficients of determination R2 of 0.893 for 930 log(Mw/IBC50) in the training set, 0.723 for 306 log(Mw/IBC50) in the test se, and 0.865 for 1236 toxicity log(Mw/IBC50) in the total set. The optimal RF global model proposed in this work is comparable to other published local QSTR models on small datasets of the toxicity to Vibrio fischeri. [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]

Purpose: Unbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry. Design/methodology/approach: The identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance. Findings: The proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage. Originality/value: The data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement. [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]

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 of objective world, as well as the ambiguity of human thinking, the practical decision-making issues become more and more difficult. Pythagorean fuzzy set is an effective tool for depicting uncertainty of the multi-criteria decision-making problems. This study aims to develop a Pythagorean fuzzy multi-criteria decision-making approach to deal with decision-making problem under uncertainty circumstance. Firstly, the concept, representation and related properties of Spearman rank correlation coefficient (SRCC) originated from statistical theory between two PFSs are introduced, which is used to measure the closeness degree between ideal alternative and each alternative. Then, a multi-criteria decision-making approach with Pythagorean fuzzy environment is developed based on the proposed SRCC. Finally, to illustrate the applicability and effectiveness of the proposed method, a real-world infrastructure project decision-making was demonstrated. The result shows that the main advantage of the proposed decision rule would reduce the complexity of the decision-making problem both in theory and practice. [ABSTRACT FROM AUTHOR]

The nonnegative matrix factorization (NMF) has been widely used because it can accomplish both feature representation learning and dimension reduction. However, there are two critical and challenging issues affecting the performance of NMF models. One is the selection of matrix factorization rank, while most of the existing methods are based on experiments or experience. For tackling this issue, an adaptive and stable NMF model is constructed based on an adaptive factorization rank selection (AFRS) strategy, which skillfully and simply integrates a row constraint similar to the generalized elastic net. The other is the sensitivity to the initial value of the iteration, which seriously affects the result of matrix factorization. This issue is alleviated by complementing NMF and deep learning each other and avoiding complex network structure. The proposed NMF model is called deep AFRS-NMF model for short, and the corresponding optimization solution, convergence and stability are analyzed. Moreover, the statistical consistency is discussed between the rank obtained by the proposed model and the ideal rank. The performance of the proposed deep AFRS-NMF model is demonstrated by applying in genetic data-based tumor recognition. Experiments show that the factorization rank obtained by the deep AFRS-NMF model is stable and superior to classical and state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Purpose: To achieve sustainability for a construction project requires the achievement of economic, environmental and social sustainability at the same time. The economic sustainability of a project should be built into the stipulated cost. The unbalanced bidding always contribute cost overrun for a construction project. The purpose of this paper is to develop a method for identifying unbalanced bidding. Design/methodology/approach: The problem of identifying unbalanced bidding is a comprehensive evaluation problem. All line items and bidders in bills of quantities are evaluation factors and evaluation objects, respectively, and the engineer's estimated prices are considered as the evaluation benchmarks. The weights of these factors are determined through integrating the entropy weight method and the analytic hierarchy model, which consider subjective and objective factors in the weighting process. Findings: The proposed model can be used to quantitatively evaluate unbalanced bids. The identification process can be analyzed within a short period, specifically with the aid of Microsoft Excel, reducing delays in awarding contracts. The results show that the model will support owners as they efficiently and effectively identify unbalanced bids in the bid evaluation stage to mitigate the negative consequences of unbalanced bidding. Practical implications: A case study is given to verify the feasibility and practicability of the proposed method, which not only assists owners in efficiently and effectively identifying unbalanced bidding, but also promotes the economic sustainability of construction projects. Originality/value: The fuzzy comprehensive evaluation method is used to detect unbalanced bidding, allowing owners to be objective as they identify and reduce unbalanced bidding at the procurement stage. [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]

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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]

The internal concentration represented by the critical body residue (CBR) is an ideal indicator to reflect the intrinsic toxicity of a chemical. Whilst some studies have been performed on CBR, the effect of exposure route on internal toxicity has not been investigated for fish. In this paper, acute toxicity data to fish comprising LC and LD values were used to investigate CBR. The results showed that exposure route can significantly affect the internal concentration. LD and CBR calculated from LC and BCF both vary independently of hydrophobicity as expressed by log K; conversely, LC is related to log K. A poor relationship was observed between LC and LD, but the relationship can be improved significantly by introduction of log K because log CBR is positively related to log LD. The parallel relationship of log CBR-log K and log LD-log K indicates that LD does not reflect the actual internal concentration. The average LD is close to the average CBR for less inert and reactive compounds, but greater than the average CBR for baseline compounds. This difference is due to the lipid fraction being the major storage site for most of the baseline compounds. Investigation on the calculated and observed CBRs shows that calculated CBRs are close to observed CBRs for most of compounds. However, systemic deviations of calculated CBRs have been observed for some compounds. The reasons for these systemic deviations may be attributed to BCF, equilibrium time and experimental error of LC. These factors are important and should be considered in the calculation of CBRs. [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]

Quantitative structure-activity relationships (OSARs) for the toxicity of substituted phenols, anilines and nitrobenzenes to algae (Scenedesmus obliquus) have been studied. Chemicals were divided into polar narcotics and electrophiles based on structure criteria according to the toxicity mechanisms of action. A good relationship between the toxicity and octanol/water partition coefficient (logP) was observed for the polar narcotic compounds. The results confirmed that hydrophobicity is the determining physicochemical parameter in modelling narcotics. However, no statistically significant mono-parametric QSAR models could be made from descriptors calculated in this study for all the compounds. In order to investigate the mechanisms of toxic action and develop OSAR models for all compounds, Abraham solvation descriptors were calculated from the program of Pharma-Algorithms. Stepwise regression produced a three-parameter QSAR model (polarizability/dipolarity, hydrogen-bond basicity and molecular volume) with a good statistical fit for all the compounds studied, which had square of the correlation coefficient R²=0.83. We have also developed an interpretable QSAR model by using parameter of logP, which represents the bio-uptake process, and polarizability/dipolarity (8), which represents the irteraction of chemicals with the acceptor micromolecules (target receptor) at the active site. No hydrogen-bond interaction was observed between the chemicals and receptor micromolecules. [ABSTRACT FROM AUTHOR]

An appropriate project delivery system plays an essential role in sustainable construction project management. Due to the complexity of practical problems and the ambiguity of human thinking, selecting an appropriate project delivery system (PDS) is an enormous challenge for owners. This paper aims to develop a PDS selection method to deal with the related-indicators case by combining the advantages of Pythagorean fuzzy sets (PFSs) and Pythagorean fuzzy weighted Muirhead mean (PFWMM) operators. The contributions of this paper are as follows: (1) This study innovatively introduced the PFWMM operator to deal with PDS selection problems for the case of the relevance among all indicators affecting PDSs selection in a complex environment. (2) A new method of solving indicators' weights was proposed to adapt to the related-indicators PDS selection problem, through investigating the differences between the ideal PDS and the alternative PDS under all indicators. (3) A decision-making framework for PDS selection was constructed by comprehensive use of the advantages of PFSs and the PFWMM operator in dealing with related-indicators PDS decision-making problems. An example of selecting a PDS is exhibited to illustrate the effectiveness and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

The Markov random field model (MRF) has attracted a lot of attention in the field of remote sensing semantic segmentation. But, most MRF-based methods fail to capture the various interactions between different land classes by using the isotropic potential function. In order to solve such a problem, this paper proposed a new generalized probability inference with an anisotropic penalty for the object-based MRF model (OMRF-AP) that can distinguish the differences in the interactions between any two land classes. Specifically, an anisotropic penalty matrix was first developed to describe the relationships between different classes. Then, an expected value of the penalty information (EVPI) was developed in this inference criterion to integrate the anisotropic class-interaction information and the posteriori distribution information of the OMRF model. Finally, by iteratively updating the EVPI terms of different classes, segmentation results could be achieved when the iteration converged. Experiments of texture images and different remote sensing images demonstrated that our method could show a better performance than other state-of-the-art MRF-based methods, and a post-processing scheme of the OMRF-AP model was also discussed in the experiments. [ABSTRACT FROM AUTHOR]

Project procurement method (PPM) selection influences the efficiency of project implementation. Owners are presented with different options for project delivery. However, selecting the appropriate PPM poses great challenges to owners, given the existence of ambiguous information. The interval neutrosophic set (INS) shows power to handle imprecise and ambiguous information. This paper aims to develop a PPM selection model under an interval neutrosophic environment for owners. The main contributions of this paper are as follows: (1) The similarity measure is innovatively introduced with interval neutrosophic information to handle the PPM selection problem. (2) The similarity measure based on minimum and maximum operators is applied to construct a decision-making model for PPM selection, through considering the truth, falsity, and indeterminacy memberships simultaneously. (3) This study establishes a PPM selection method with INS by applying similarity measures, that takes account into the determinacy, indeterminacy, and hesitation from the decision experts when giving an evaluation value. A case study on selecting PPM is made to show the applicability of the proposed approach. Finally, the results of the proposed method are compared with those of existing methods, which exhibit the superiority of the proposed PPM selection method. [ABSTRACT FROM AUTHOR]

Interval Pythagorean fuzzy set (IPFS), which can handle imprecise and ambiguous information, has attracted considerable attention in both theory and practice. However, one of the main difficulties under IPFSs is the comparison between interval numbers. To overcome this shortcoming, connection number theory is first introduced, and interval numbers are transformed into connection numbers in the operating process. Considering that similarity measures play an important role in assessing the degree between ideal and proposal alternatives in the decision making process, this paper aims to develop new similarity measures with IPFSs and apply them to multi-criteria decision making (MCDM) problems. The main contributions of this paper are as follows: (1) introduction of a comparison method through transforming interval numbers into connection numbers; (2) development of three new similarity measures with IPFSs based on the minimum and maximum operators, and investigation of their properties; (3) calculation of the similarity measures considering weights of membership and non-membership degrees; (4) establishment of an interval Pythagorean fuzzy decision making method applying the presented similarity measures. A case study on selecting a project delivery system is made to show the applicability of the proposed approach. [ABSTRACT FROM AUTHOR]