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Abstract Background There have been few longitudinal studies on Chinese bus drivers and the individual differences in the relationships between organizational justice and job satisfaction. This study examined the organizational justice and job satisfaction in bus drivers and the individual differences in this relationship. Methods A two-wave longitudinal study design was employed. A first survey was conducted on 513 Chinese bus drivers in October 2021 that collected socio-demographic information and asked about their perceptions of organizational fairness. A second survey was conducted six months later that asked about role overload and job satisfaction and assessed their proactive personality type. An effect model was then used to explore the moderating effects of role overload and proactive personality type on the relationships between organizational justice and job satisfaction. Results Both procedural and interactive justice predicted the bus drivers’ job satisfaction. Proactive personalities and role overload were found to enhance this relationship. Conclusions Organizations could benefit from screening at the recruitment stage for drivers with highly proactive personalities. Relevant training for drivers with low proactive personalities could partially improve employee job satisfaction. When viewed from a Chinese collectivist cultural frame, role overload could reflect trust and a sense of belonging, which could enhance job satisfaction. Finally, to improve employee job satisfaction, organizations need to ensure procedural and interactive justice.

Abstract Multi-packer completion strings have played a pivotal role in secure exploitation of oil and gas, increasing production and mitigating greenhouse gas emissions. While the integration of multi-packer structures has proven advantageous in oil and gas exploration, it has introduced complexities in load distribution, consequently giving rise to safety concerns. This study undertakes a thorough examination of the mechanical analysis pertaining to multi-packer completion strings. We present an analytical model for predicting the axial forces acting on the multi-packer string, utilizing the geometric constraint arising from the immobility of packers. It is demonstrated that the pressure differentials at the packers exhibit uniqueness in relation to both initial and boundary conditions, as well as the geometrical constraint. This paper provides an analytical solution for these pressure differentials. Novel concepts regarding the eigen-matrix of an N-packer completion string, influenced solely by Poisson’s ratio, a virtual $$(N+1)$$ ( N + 1 ) th packer and the eigen-depth and eigen-ratio of two adjacent packers, are proposed and their applications are discussed. Furthermore, this paper delves into a deeper examination of the multi-packer string’s underlying mechanism. A consistent algorithm grounded in geometric analysis is developed based on the analytical model. Validation of our model is performed using three practical cases across various operation conditions, and the results demonstrate the efficacy of this methodology in accurately predicting failure occurrences. Sensitivity analysis results further substantiate the robustness of this method in practical applications. Additionally, it has been shown that strategically positioning the packers in areas where the string is highly prone to fractures significantly enhances the safety of the multi-packer string system. The findings presented in this paper offer a foundational framework for analyzing the mechanical behavior of constrained strings. Furthermore, there is potential for the development of the analytical model to incorporate additional factors, such as string system with packers of semi-free or free movement. The proposed method is also of fundamental significance for safety evaluation of string systems in carbon storage projects, which is obtaining increasing attention in the context of carbon neutralization.

The “campus loans” crisis has highlighted the importance of financial literacy among Chinese college students. Based on an analysis of 2,266 valid questionnaires, this study utilized survey data and logistic regression to examine the correlations between demographic and behavioral factors and financial literacy among students. The results indicated that, compared to their international counterparts, Chinese students generally possess less financial knowledge. However, they exhibit stronger financial attitudes and behaviors. A significant gender disparity was observed, with female students outperforming male students in financial literacy. Students attending more prestigious universities, particularly those majoring in economics, management, science, and engineering, and those dedicating more time to financial education, showed higher levels of financial literacy. Additionally, positive social interactions were associated with enhanced financial literacy. The study also identifies a “Surrounding People Effect,” where the presence of financially knowledgeable peers, friends, and family correlates with improved financial literacy among college students. These findings offer critical insights for developing targeted policies to enhance financial literacy among Chinese college students.

Background: More than half the domestic population in China were infected with COVID-19 in two months after ending “zero-infection policy”, which severely overwhelmed frontline healthcare providers with stress and fear. However, there is no study to date investigating the associations between nurses' fear of pandemic and cyberchondria. This study aimed to 1) investigate the correlations between fear pandemic and cyberchondria among frontline nurses, and 2) discover its potential mechanism. Methods: A cross-sectional sample of frontline nurses (N = 8161) was recruited from 98 hospitals across China in February 2023. Participants were invited to complete an online, self-rated standardized questionnaire focused on pandemic fear, alexithymia, psychological distress, and cyberchondria. Environmental, clinical and socioeconomic information were collected for adjustment while conducting chain mediation analysis. Results: When other covariates were controlled, it was found that fear of the pandemic significantly contributed to cyberchondria (b = 0.58, 95%CI [0.56, 0.60], p

Abstract Natural gas distributed energy is recognized as a pivotal means to enhance energy efficiency and mitigate carbon dioxide emissions through localized energy cascading. Positioned as a key option for advancing the Sustainable Development Goals, this system optimizes energy utilization near end-users. While maximizing energy efficiency, it is imperative to address potential environmental challenges. A thorough, comprehensive environmental assessment, facilitated by the life cycle assessment method, proves instrumental in meeting this standard. Employing this method enables an intuitive grasp of the environmental strengths and weaknesses inherent in natural gas distributed energy within the power structure. This insight serves as a foundation for informed project decision-making, fostering the growth of the industry. We selected six environmental impact assessment categories based on the CML 2001 method, and conducted the life cycle analysis across four stages. China's inaugural natural gas distributed energy demonstration project was chosen as a model case, and an environmental impact assessment inventory was established, utilizing survey data and literature for comprehensive data collection and analysis. Results from case testing yield environmental impact assessment outcomes, with a specific sensitivity analysis for stages with notable environmental impact factors. The study underscores that the operation phase has the highest environmental impact, comprising 78.37% of the total combined environmental impact, followed by the fuel production phase. Comparative analyses with coal-fired and conventional natural gas power generation, based on dimensionless literature data, reveal that abiotic resources depletion potential is the primary contributor to the environmental impact of 1 kWh of electricity product, constituting 52.76% of the total impact value, followed by global warming potential. Concrete strategies have been outlined for decision-making in both the operational and planning phases of natural gas distributed energy projects. The strengthening of policies is pinpointed towards grid connection and scale expansion.

With the trend of national cultural confidence and the growing appreciation for aesthetic diversity, traditional apparel from different countries or regions has become a driving force in the clothing industry. Hanfu, an emerging trend that industrializes traditional culture, has garnered increasing attention from consumers. Thus, with the objective of exploring the psychological antecedents of Hanfu consumers’ purchase intentions from the perspectives of product identification, cultural motivation, and consumers’ perceived authenticity, the present study was empirically conducted with a sample of 823 respondents. Partial least squares-structural equation modeling (PLS-SEM) was employed to examine the proposed research model. The results demonstrate that consumers’ identification with Hanfu and cultural motivation positively influence object-based and existential authenticity, as well as purchase intention. Furthermore, the mediating effect of perceived object-based authenticity is confirmed, indicating its significance in shaping consumers’ purchase intentions, while the mediating effect of existential authenticity is found to be insignificant. Research findings could contribute to the understanding of the psychological mechanisms driving consumers’ purchase intentions towards traditional clothing and highlight the importance of consumers’ perceived object-based authenticity in the market of traditional cultural clothing.

Controlling rumors is related to the interplay between the rumor and rumor refutation, which compete to attract the unaware. And rumor refutation preys on the rumors, and try to eliminate rumors. Therefore, there is both a predatory and competitive relationship between the rumors and the rumor refutations. This paper presents a model based on biomathematics theory to describe the interplay between rumors and rumor refutations. The theoretical analysis of the differential equations elucidated three dynamic cases: rumor extinction; rumor refutation extinction; and rumor and rumor refutation coexistence. The subsequent analysis of the equilibrium stability in the three cases revealed both equilibrium stability and model instability. The haze rumor and the official haze refutation data were then crawled from Sina microblog, the rumor propagation process analyzed, an integral method employed for the model parameter estimation, and the proposed model used to estimate and forecast the haze rumor and rumor-refutation evolutions. The findings suggested that rumors and rumor refutations coexist, which was consistent with the theoretical analysis of coexistence. Based on this case and to more deeply analyze the effect of an authority's credibility and the public's cognition, the proposed model was used to suggest several scenarios, and policy suggestions given to assist authorities better manage rumors in emergency events.

As starting university is a critical independence milestone for many young people, it would also be the best time to provide them with some financial education (FE). Although there have been many initiatives aimed at enhancing individual financial literacy (FL) and/or financial decision-making, meta-analyses have shown that the effectiveness of FE has been mixed. This study examined the driving forces behind the decision by college students to enroll in a targeted financial literacy curriculum (FLC) and the impact of this attendance on their FL. An endogenous switching model (ESM) was employed to account for the heterogeneity in the decision to attend or not attend the FLC and to counteract any unobservable characteristics. It was found that students with higher self-perceived FL did not prefer to attend the FLC; however, for others, FLC attendance was found to significantly boost their FL in areas such as financial knowledge (FK), financial attitude (FA), and financial behavior (FB), especially for the non-attendees under the counterfactual framework. These “non-attendees” were observed to have some characteristics (e.g., prior knowledge) that made them more financially literate regardless of attendance; however, if they had attended the FLC, they would have gained a greater FL than the attendees. As the FL of the attendees would have been much lower if they had not attended, the FLC appeared to be particularly important for the attendees, which strengthened the case for making the FLC a compulsory part of a general college education.

The consistency test is a vital component of pairwise comparison matrices if meaningful results are to be guaranteed, and it has been studied extensively, since the analytic hierarchy process was developed by Saaty. However, how to deal with the consistency of a probability-hesitant analytic hierarchy process with different probability values is a specific problem which needs to be studied further. This paper provides a direct consistency test and an improvement method for the probability-hesitant analytic hierarchy process. A paradox in Saaty's consistency test is first proposed, and then a direct consistency improvement method is suggested for dealing with the consistency of a probability-hesitant analytic hierarchy process with different probability values, from the perspective of three tuples, rather than carrying out matrix operations. In our method, only simple mathematical calculations are needed and there is no need for matrix operations. By using a partial correction, the proposed method can retain most of the information provided by the original comparison matrix, and simultaneously indicate the modification direction and provide the optimal values. At the same time, using the proposed method, the inconsistent elements in the probability-hesitant pairwise comparison matrix can be found rapidly and with a high degree of accuracy. Moreover, our proposed iterative algorithm is a method that is both very quick and leads to good results being obtained.

The analysis and evaluation of agricultural drought risk can assist in reducing regional disasters and agricultural drought losses. Because of the uncertainties and incomplete agricultural drought information, this paper employed an information diffusion technology and information matrix to identify a drought disaster risk distribution and to quantify the relationship between the annual drought-affected rate and the grain production losses in China's major grain-producing areas. From the assessment results, provincial drought disaster risk spatial distribution maps for each major grain-producing area in China were obtained. These risk patterns showed that the probability of drought fell when the annual drought-covered rate and the annual drought-affected rate increased, and that the high risk areas were located primarily in China's northern and central provinces. These results can provide the basis for the development of effective drought mitigation strategies which would be able to inform possible drought situations and allow for easier decision-making on drought resistance strategies. The fuzzy relationship between the annual drought-affected rate and the drought-caused grain production losses provides vital information for the development of disaster compensation plans. Furthermore, the results of this study indicated that the proposed methods had superior detection stability and higher precision. We hope that by conducting such agricultural drought risk analysis, the results are able to provide the basis for the development of drought mitigation strategies to reduce future losses.

Abstract Background In this study, exposure refers to survivors who suffered from life-changing situations, such as personal injuries, the deaths or injury of family members, relatives or friends or the loss of or damage to personal or family property, as a result of the earthquake. The mediating effect of risk perception on the exposure and psychological health in survivors from the Longmen Shan Fault area and the moderating effect of social support on the relationship between risk perception and psychological health were both examined. Method A cross-sectional survey was conducted in a local Longmen Shan Fault area near the epicenter of the 2008 Wenchuan earthquake. The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), the standard Chinese 12-item Short Form (SF-12v2), and the Social Support Rating Scale (SSRS) were used to interview 2,080 earthquake survivors in the period one-year after the earthquake. Based on the environment and the characteristics of the Longmen Shan Fault area, a risk perception questionnaire was developed to evaluate survivor risk perception. Factor and regression analyses were conducted to determine the hypothetical relations. Results The analyses provided effective support for the hypothesized model. Survivor risk perception was classified into direct risk perception and indirect risk perception. Survivor direct risk perception was found to play a partial mediating role in the relationship between exposure and the two domains (Physical component summary (PCS) and the Mental component summary (MCS)) of psychological health. Survivor indirect risk perception was found to have a only partial mediating effect on the association between exposure and MCS. Social support was found to moderate the influence of risk perception on psychological health. Conclusion Risk communication should be considered in future post-earthquake psychological assistance programs and social support strategies could also be useful in improving psychological health.

Sustainable supply chain network design has attracted great attention of academia and industry in recent years. Baijiu is one of the world’s oldest distilled alcoholic beverages and plays a significant role in Chinese culture and Chinese people’s daily life. As the production and consumption of Baijiu have a significant influence on the economic, environmental, and social performance of supply chain management, sustainable supply chain network design decisions are critical to the long-term success of the industry. In concert with the rapidly growing Chinese economy, there is a growing demand for a sustainable Baijiu industry. Therefore, this paper constructs and optimizes a network decision-support model for a sustainable Baijiu industry network design. To achieve this, the Baijiu supply chain is examined and a model is proposed for a design that encompasses economic (costs), environmental (carbon emissions), and social (local employment and regional per capita GDP) dimensions. R language programming is then applied to solve the model. A case example indicated that S1 was the optimal decision for reducing costs, S2 was the optimal solution for minimizing carbon emissions, and S3 was the best for maximizing the social impact. Considering the situation of the Baijiu industry and the focal enterprise, it was concluded that S1 would be the best solution for the case company. And the results verified the effectiveness of the framework. This paper develops a systematic and effective approach that decision-makers can use to conduct sustainable network design for Baijiu enterprises.

Because of the impending energy crisis and the environmental problems caused by the excessive use of fossil fuels, biofuels produced from renewable energy biomass have been playing a more significant role in the world. This follows from their obvious environmental and economic advantages. Bioethanol, the most widely used transportation biofuel, is typically derived from plant-based feedstock sources such wheat, sugar beet, corn, straw, and wood. However, the main problem with bioethanol production is that despite the range of feedstock, raw material availability varies considerably from season to season, as there is no systematic framework. By combining technological paradigm theory with literature mining, we found that bioethanol feedstock production development has followed a three-stage trajectory, which is in accordance with the traditional technological paradigm – the S-curve. This new curve can be divided into BFDP (bioethanol feedstock development paradigm) competition, BFDP diffusion, and BFDP shift. Each phase has a different generation of feedstock; first-generation bioethanol in BFDP competition, second-generation bioethanol in BFDP diffusion, and third-generation bioethanol in BFDP shift. Further, based on the technological support, literature mining, and a realistic background, the second-generation bioethanol (mainly lignocellulosic biomass) is expected to continue to be a significant future trend in the world. The new BFDP framework presented in this paper may provide scholars with research ideas for the future.

In the emerging supply chain environment, green supply chain risk management plays a significant role than ever. Risk is an inherent uncertainty and has tendency to disrupt the typical green supply chain management (GSCM) operations and eventually reduce the success rate of industries. In order to mitigate the consequences, a fuzzy multi-criteria group decision making modeling (FMCGDM) which could evaluate the potential risks in the context of (GSCM) is needed from the industrial point of view. Therefore, this research proposes a combined fuzzy analytical hierarchy process (AHP) to calculate the weight of each risk criterion and sub-criterion and technique for order performance by similarity to ideal solution (TOPSIS) methodology to rank and assess the risks associated with implementation of (GSCM) practices under the fuzzy environment. The proposed fuzzy risk-oriented evaluation model is applied to a practical case of textile manufacturing industry. Finally, the proposed model helps the researchers and practitioners to understand the importance of conducting appropriate risk assessment when implementing green supply chain initiatives.

The world’s energy needs have been continually growing over the past decade, yet fossil fuels are limited. Renewable energies are becoming more prevalent, but are still a long way from being commonplace worldwide. Literature mining is applied to review carbon capture and storage (CCS) development trends and to develop and examine a novel carbon capture and storage technological paradigm (CCSTP), which incorporates CCSTP competition, diffusion and shift. This paper first provides an overview of the research and progress in CCS technological development, then applies a techno-paradigm theory to analyze CCSTP development and to provide a guide for future CCS technological trends. CCS could avoid CO2 being released into the atmosphere. Moreover, bioenergy with CCS (BECCS) can make a significant contribution to a net removal of anthropogenic CO2 emissions. In this study, we compare the different CCSTP developmental paths and the conventional techno-paradigm by examining the S-curves. The analyses in this paper provide a useful guide for scholars seeking new inspiration in their research and for potential investors who are seeking to invest research funds in more mature technologies. We conclude that political barriers and public acceptance are the major distinctions between the CCSTP and the conventional techno-paradigm. It is expected that policy instruments and economic instruments are going to play a pivotal role in the accomplishment of global carbon reduction scenarios.

Purpose: The aim of this paper is to deal with the supply chain management (SCM) with quantity discount policy under the complex fuzzy environment, which is characterized as the bi-fuzzy variables. By taking into account the strategy and the process of decision making, a bi-fuzzy nonlinear multiple objective decision making (MODM) model is presented to solve the proposed problem.Design/methodology/approach: The bi-fuzzy variables in the MODM model are transformed into the trapezoidal fuzzy variables by the DMs's degree of optimism ?1 and ?2, which are de-fuzzified by the expected value index subsequently. For solving the complex nonlinear model, a multi-objective adaptive particle swarm optimization algorithm (MO-APSO) is designed as the solution method.Findings: The proposed model and algorithm are applied to a typical example of SCM problem to illustrate the effectiveness. Based on the sensitivity analysis of the results, the bi-fuzzy nonlinear MODM SCM model is proved to be sensitive to the possibility level ?1.Practical implications: The study focuses on the SCM under complex fuzzy environment in SCM, which has a great practical significance. Therefore, the bi-fuzzy MODM model and MO-APSO can be further applied in SCM problem with quantity discount policy.Originality/value: The bi-fuzzy variable is employed in the nonlinear MODM model of SCM to characterize the hybrid uncertain environment, and this work is original. In addition, the hybrid crisp approach is proposed to transferred to model to an equivalent crisp one by the DMs's degree of optimism and the expected value index. Since the MODM model consider the bi-fuzzy environment and quantity discount policy, so this paper has a great practical significance.

The location of temporary facilities on construction sites is essential to the enhancement of productivity and safety, but it is complex due to the unique issues associated with construction. To positively contribute to the dynamic construction site layout planning field, this paper proposes a new fuzzy multi-objective decision making model. The proposed hybrid optimization model utilizes fuzzy numbers and logic to represent the closeness relationship between temporary facilities. The two main phases presented represent a specific advance in knowledge in through: (1) an opti­mization model that considers both uncertainty and dynamic elements; (2) the application of this optimization to a spe­cial project. A multi-objective simulated annealing-based genetic algorithm (MOSA-based GA) is proposed to solve the model and the case of Jinping-II hydroelectric station is studied to evaluate the model’s performance. The computational study was carried out to demonstrate the practicality and efficiency of the proposed optimization method. The study is applicable and useful to the profession.

This paper discusses a two-stage based dynamic transportation assignment problem (TS-based DTAP) under a fuzzy random environment in an earth-rock transportation system. This problem is a multi-objective dynamic programming optimization process for minimizing total operational cost, transportation duration and total waste. Triangular fuzzy random numbers are used for the uncertain parameters, and a hybrid crisp approach and an expected value operator are introduced to deal with these uncertainties. A dynamic programming based contraction particle swarm optimization is developed to solve the proposed expected value model for TS-based DTAP. Then, the earth-rock dam construction at Pubugou Hydropower project is used as a practical application to verify the proposed approach. Results and analysis are presented to highlight the performance of the proposed TS-based DTAP model and the optimization method, which proves to be effective and relatively efficient compared to the models under other environments and a standard PSO algorithm.

This paper proposes a rumor spreading model which examines how the memory effects rate changes over time in artificial network and a real social network. This model emphasizes a special rumor spreading characteristic called “the cumulative effects of memory.” A function p(t) reflecting the cumulative memory effects is established, which replaces the constant rate of memory effects in the traditional model. Further, rumor spreading model simulations are conducted with different parameters in three artificial networks. The results show that all the parameters but the initial memory rate of memory effects function have a significant impact on rumor spreading. At the same time, the simulation results show that the final size of the stiflers is sensitive to the average degree k when it is small but is not sensitive to k when the average degree is greater than a certain degree. Finally, through investigations on the Sina Microblog network, the numerical solutions show that the peak value and final size of the rumor spreading are much larger under a variable memory effects rate than under a constant rate.

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method.

This paper focuses on the problem of hedging against seismic risk through the retrofit of transportation systems in large-scale construction projects (LSCP). A fuzzy random multiobjective bilevel programming model is formulated with the objectives of the retrofit costs and the benefits on two separate levels. After establishing the model, a fuzzy random variable transformation approach and fuzzy variable approximation decomposition are used to deal with the uncertainty. An approximation decomposition-based multi-objective AGLNPSO is developed to solve the model. The results of a case study validate the efficiency of the proposed approach.

The aim of this paper is to deal with the optimal navigation coordinated scheduling (NCS) problem in ship transportation of the Three Gorges Project in China, i.e. the Three Gorges Dam and the Gezhouba Dam. The NCS includes operational scheduling for two five-step locks in Three Gorges Dam and three single-step locks in Gezhouba Dam. A birandom multiple objective decision-making model is first proposed for the NCS problem to cope with hybrid uncertain environment where twofold randomness exists in practice. Then, particle swarm optimization is applied to search for the optimal solution. Based on real execution data, the results generated by a computer validate effectiveness of the proposed model and algorithm in solving large-scale practical problems is presented.

BACKGROUND: On May 12th 2008, an earthquake with a magnitude of 8.0 on the Richter scale struck China, causing a large number of casualties and significant economic losses. By interviewing 2080 survivors of Wenchuan earthquake, the objective of this study is to estimate the role of different types of social support as possible moderating factors between anxiety and depression. METHODS: A stratified random sampling strategy about the cross-sectional study was adopted. The self-rating anxiety scale (SAS), Self-Rating Depression Scale (SDS) and Social Support Rating Scale (SSRS) were used. A total of 2080 adult survivors of the Wenchuan earthquake from 19 damaged countries participated in the survey. Correlation analysis and regression analysis were performed to evaluate the moderating role of social support on the relationship between anxiety and depression. RESULTS: One year after the Wenchuan earthquake, anxiety and depression were found to be 37.6% and 40.7%, respectively. Demographic characteristics were seen as significant in the cases of depression, except for age (p=0.599), while age and education level were not found to be significant for anxiety. The results showed that social support, especially subjective support could moderate the association between anxiety and depression. CONCLUSIONS: Social support should be particularly focused on female survivors, those of the Han ethnic group, and those with a lower level of education and a lower income. Psychological intervention and care for survivors should focus on those most disoriented by the disaster.

The destruction of the natural environment has been drawing more and more attention. Developing low-carbon industry chains is an effective solution to the conflict between rapid economic growth and high CO2 emissions. Summarizing various traditional and new industry chain sustainable development, live pig industry was chosen as a typical industry chain to study low-carbon development using a system dynamics and random chance-constrained model (SD-RCCM). Leshan, a world natural and cultural heritage area in China, was selected as a typical city to analyze the low-carbon pig industry. Three different programs based on distribution ratios were selected to study this industry. The results showed that program 1, which considers both environmental and economic benefits, realizes sustainable development. In order to extend the pig industry chain and fully utilize pig ordure and other waste, introducing a Clean Development Mechanism (CDM) and household biogas exploitation program is recommended.

The axial stress and deformation of high temperature high pressure deviated gas wells are studied. A new model is multiple nonlinear equation systems by comprehensive consideration of axial load of tubular string, internal and external fluid pressure, normal pressure between the tubular and well wall, and friction and viscous friction of fluid flowing. The varied temperature and pressure fields were researched by the coupled differential equations concerning mass, momentum, and energy equations instead of traditional methods. The axial load, the normal pressure, the friction, and four deformation lengths of tubular string are got ten by means of the dimensionless iterative interpolation algorithm. The basic data of the X Well, 1300 meters deep, are used for case history calculations. The results and some useful conclusions can provide technical reliability in the process of designing well testing in oil or gas wells.

An equilibrium chance-constrained multiobjective programming model with birandom parameters is proposed. A type of linear model is converted into its crisp equivalent model. Then a birandom simulation technique is developed to tackle the general birandom objective functions and birandom constraints. By embedding the birandom simulation technique, a modified genetic algorithm is designed to solve the equilibrium chance-constrained multiobjective programming model. We apply the proposed model and algorithm to a real-world inventory problem and show the effectiveness of the model and the solution method.

A coupled system model of partial differential equations is presented in this paper, which concerns the variation of the pressure and temperature, velocity, and density at different times and depths in high temperature-high pressure (HTHP) gas-liquid two-phase flow wells. A new dimensional splitting technique with Eulerian generalized riemann problem (GRP) scheme is applied to solve this set of conservation equations, where Riemann invariants are introduced as the main ingredient to resolve the generalized Riemann problem. The basic data of “X well” (HTHP well), 7100 m deep, located in Southwest China, is used for the case history calculations. Curve graphs of pressures and temperatures along the depth of the well are plotted at different times. The comparison with the results of Lax Friedrichs (LxF) method shows that the calculating results are more fitting to the values of real measurement and the new method is of high accuracy.

This paper studies the innovation diffusion problem with the affection of urbanization, proposing a dynamical innovation diffusion model with fuzzy coefficient, and uses the shifting rate of people from rural areas stepping into urban areas to show the process of urbanization. The numerical simulation shows the diffusion process for telephones in China with Genetic Algorithms and this model is effective to show the process of innovation diffusion with the condition of urbanization process.

Invex monotonicity and pseudoinvex monotonicity of fuzzy mappings are introduced in this paper, and relations are discussed between invex monotonicity (pseudoinvex monotonicity) and invexity (pseudoinvexity) of fuzzy mappings. The existence of a solution to the fuzzy variational-like inequality is discussed, and the existence theorem can be achieved. Furthermore, some extended properties of the fuzzy variational-like inequality are researched. Finally, method of solution is discussed based on genetic algorithm.

This paper focuses on the development of a bilevel optimization model with random coefficients for a production-inventory system. The expected value operator technique is used to deal with the objective function, and rough approximation is applied to convert the stochastic constraint into a crisp constraint. Then an interactive programming method and genetic algorithm are utilized to solve the crisp model. Finally, an application is given to show the efficiency of the proposed model and approaches in solving the problem.

OBJECTIVE: By testing the mediating effect of coping strategies on the relationship between social support (SS) and posttraumatic growth (PTG), the aim of this research was to develop a new approach for the study of post-disaster psychological intervention. METHODS: A mediating effect model analysis was conducted on 2080 adult survivors selected from 19 of the counties hardest-hit by the 2008 Wenchuan earthquake. The Social Support Rating Scale and the Coping Scale were used to predict the PTG. RESULTS: A bivariate correlation analysis showed that there was a correlation between posttraumatic growth, social support and coping strategies. The mediation analysis revealed that coping strategies played a mediating role between social support and posttraumatic growth in survivors after the earthquake. CONCLUSION: The results demonstrated that mental health programs for survivors need to focus on the establishment of a good social support network, which was found to be conductive to maintaining and increasing mental health levels. At the same time, adequate social support is able to assist survivors in adopting mature coping strategies, such as problem solving and asking for help. Hence, social support was found to play a vital role in balancing and protecting mental health.

This paper focuses on a multiproject resource allocation problem in a bilevel organization. To solve this problem, a bilevel multiproject resource allocation model under a fuzzy random environment is proposed. Two levels of decision makers are considered in the model. On the upper level, the company manager aims to allocate the company's resources to multiple projects to achieve the lowest cost, which include resource costs and a tardiness penalty. On the lower level, each project manager attempts to schedule their resource-constrained project, with minimization of project duration as the main objective. In contrast to prior studies, uncertainty in resource allocation has been explicitly considered. Specifically, our research uses fuzzy random variables to model uncertain activity durations and resource costs. To search for the optimal solution of the bilevel model, a hybrid algorithm made up of an adaptive particle swarm optimization, an adaptive hybrid genetic algorithm, and a fuzzy random simulation algorithm is also proposed. Finally, the efficiency of the proposed model and algorithm is evaluated through a practical case from an industrial equipment installation company. The results show that the proposed model is efficient in dealing with practical resource allocation problems in a bilevel organization.

The idea of the “garden city” was developed theoretically to offer solutions to serious city development problems such as traffic congestion, population, and environmental pollution, among which the transportation is considered the most important. The question is how to develop balanced transportation in a garden city. Transportation is a complex system, particularly in a garden city. Therefore, we establish a new approach named the transportation multiobjective optimization system dynamics (SD-MOP) model, which firstly calculates the optimal proportion of different transport means with an MOP approach and then applies them to the dynamic transportation system to analyze the results and analyze the influence on the whole system using different transportation means variation. In this paper, we take Chengdu as an example, one of the few cities in the world declared as building a garden city, and then develop some recommendations about world modern garden city transportation system development.

We concentrate on discussing a class of two-person zero-sum games with rough payoffs. Based on the expected value operator and the trust measure of rough variables, the expected equilibrium strategy and r-trust maximin equilibrium strategy are defined. Five cases whether the game exists r-trust maximin equilibrium strategy are discussed, and the technique of genetic algorithm is applied to find the equilibrium strategies. Finally, a numerical example is provided to illustrate the practicality and effectiveness of the proposed technique.