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This study examines the effect of a Medicaid disenrollment on employment, sources of health insurance coverage, and health and health care utilization of childless adults using longitudinal data from the 2004 Panel of the Survey of Income and Program Participation. From July to September 2005, TennCare, the Tennessee Medicaid program, disenrolled approximately 170,000 adults following a change in eligibility rules. Following this eligibility change, the fraction of adults in Tennessee covered by Medicaid fell by over 5 percentage points while uninsured rates increased by almost 5 percentage points relative to adults in other Southern states. There is no evidence of an increase in employment rates in Tennessee following the disenrollment. Self-reported health and access to medical care worsened as hospitalization rates, doctor visits, and dentist visits all declined while the use of free or public clinics increased. The Tennessee experience suggests that undoing the expansion of Medicaid eligibility to adults that occurred under the Affordable Care Act likely would reduce health insurance coverage, reduce health care access, and worsen health but would not lead to increases in employment.

This paper aims to further investigate the behavior and mechanism in simulated oilfield solution on CO₂ corrosion of P110 steel at various temperatures by potentiodynamic sweep and electrochemical impedance spectroscopy (EIS) measurements, especially discussing the influence of the coverage fraction of corrosion film.

Potentiodynamic sweep and EIS measurements were applied to investigate the behavior and mechanism with the effect of temperature on CO₂ corrosion of P110 steel in simulated oilfield solution at 30°C, 60°C and 90°C.

The corrosion parameters of polarization curves, such as corrosion potential (Ecorr), corrosion current density (icorr), anodic and cathodic branches slopes (βa and βc), were analyzed and discussed in detail. In addition, the equivalent circuit models and ZsimpWin software were utilized to fit and analyze the Nyquist plots. The plots showed that corrosion potential shifted more negatively as temperature increased. The corrosion current density (icorr) initially increased and then decreased with the increase of temperature. The impedance spectra measured at various temperatures had different time constants.

The paper highlights that the coverage fraction θ of corrosion film is one most important and key variable influencing CO₂ corrosion mechanisms.

We survey banks to construct national estimates of total noncash payments by type, payments fraud and related information. The survey is designed to create aggregate total estimates of all payments in the United States using data from responses returned by a representative, random sample. In 2016, the number of questions in the survey doubled compared with the previous survey, raising serious concerns of smaller bank nonparticipation. To obtain sufficient response data for all questions from smaller banks, we administered a modified survey design which, in addition to randomly sampling banks, also randomly assigned one of several survey forms, subsets of the full survey. This case study illustrates that while several other factors influenced response outcomes, the approach helped ensure sufficient response for smaller banks. Using such an approach may be especially important in an optional-participation survey, when reducing costs to respondents may affect success, or when imputation of unplanned missing items is already needed for estimation. While a variety of factors affected the outcome, we find that the planned missing data approach improved response outcomes for smaller banks. The planned missing item design should be considered as a way of reducing survey burden or increasing unit-level and item-level responses for individual respondents without reducing the full set of survey items collected.

Media-effect refers to the phenomenon that stocks with no or low media coverage earn higher returns than stocks with high coverage. This paper aims to explore the existence of media-effect in China stock market and tests the two competing hypotheses explaining this phenomenon.

The authors construct a research sample based on a media-coverage event: the publications of lists of the most wealthy Chinese individuals; in addition, they identify the stocks of which listed firms are led by a controller who is recognized on the publicized lists. This paper uses event study methodology to test the existence of media effect in China A-share market. The authors employed propensity score matching (PSM) to construct a control group with same number of non-listed stocks. Then compared the returns of the two portfolios to test the risk premium hypothesis, and the abnormal trading volume and price reaction around the event date is explored to test the over-attention underperformance hypothesis.

Sampled stocks show significantly negative abnormal returns within the event period, but the matched control group formed by PSM shows no significant abnormal return, indicating that the risk premium hypothesis is not supported. Covered stocks show significantly magnified trading volume. The portfolio gains significant positive return before the event date but turns significantly negative afterward, which is consistent with the over-attention underperformance hypothesis.

This paper offers insights into media-effect in China stock market and provides empirical evidence explaining its existence.

The public relations industry is aware of the need for research and evaluation. It has not kept up with the relevant research and technologies which can provide a wide range of powerful R&E solutions. A number of other disciplines are becoming expert at evaluating PR. The history of development of R&E solutions for the PR industry is one of excellent opportunities largely misunderstood and little used even by a number of evaluation vendors. Reviews some current practices and offers the application of new technologies to aid the development of effective corporate communication. The proposed technology can be drawn from content and semantic analysis research and search engine development, neural networks and data‐mining software. This combines to offer powerful and effective planning research and evaluation solutions in a period of transition from print to Internet public relations practice.

The purpose of this paper is to design an inference engine to measure the level of readiness of each bank before starting the corporate sustainability auditing process. Based on the output of the designed inference engine, the audition team can decide about the audition resources and the auditing process.

In this paper, the hybrid rough and grey set theory are used to design and create a rule model system to measure the sustainability level of banks. First, 16 rule models are extracted using rough set theory (RST), and the cross-validation of each model is done. Then, the grey clustering is used to combine the same condition attributes and improve the validity of the final model. A total of 16 new rule models are extracted based on the decreased condition attributes, and the best model is selected based on the cross-validation results.

By comparing the accuracy of rough-gray’s rule models and as a result of decreasing the condition attributes, a proper increase in the accuracy of all models is obtained. Finally, the Naive/Genetic/object-related reducts model with 95.6% accuracy is selected as an inference engine to measure new banks’ readiness level.

Sustainability measurement of banks based on RST is a new approach in the field of corporate sustainability. Furthermore, using the grey clustering for combining the condition attributes is a novel solution for improving the accuracy of the rule models.

Risk management is one of the most influential parts of project management that has a major impact on the success or failure of projects. Due to the increasing use of information technology in all fields and the high failure rate of software development projects, it is essential to predict the risk level of each project effectively before starting. Therefore, the main purpose of this paper is proposing an expert system to infer about the risk of new banking software development project.

In this research, the risk of software developing projects is considered from four dimensions including risk of cost deviation, time deviation, quality deviation and scope deviation, which is examined by rough set theory (RST). The most important variables affecting the cost, time, quality and scope of projects are identified as condition attributes and four initial decision systems are constructed. Grey system theory is used to cluster the condition attributes and after data discretizing, eight rule models for each dimension of risk as a decision attribute are extracted using RST. The most validated model for each decision attribute is selected as an inference engine of the expert system, and finally a simple user interface is designed in order to predict the risk level of any new project by inserting the data of project attributes

In this paper, a high accuracy expert system is designed based on the combination of the grey clustering method and rough set modeling to predict the risks of each project before starting. Cross-validation of different rule models shows that the best model for determining cost deviation is Manual/Jonson/ORR model, and the most validated models for predicting the risk of time, quality and scope of projects are Entropy/Genetic/ORR, Manual/Genetic/FOR and Entropy/Genetic/ORR models; all of which are more than 90% accurate

It is essential to gather data of previous cases to design a validated expert system. Since data documentation in the field of software development projects is not complete enough, grey set theory (GST) and RST are combined to improve the validity of the rule model. The proposed expert system can be used for risk assessment of new banking software projects

The risk assessment of software developing projects based on RST is a new approach in the field of risk management. Furthermore, using the grey clustering for combining the condition attributes is a novel solution for improving the accuracy of the rule models.

The main purpose of the present work is to introduce two new Schiff bases as corrosion inhibitors (CIs) for carbon steel (CS). The anti-corrosion performance of these Schiff bases having N and S heteroatoms in their structures was investigated and compared in 2 M HCl electrolyte. The inhibitory activity of these Schiff bases was also assessed.

Common electrochemical assays like potentiodynamic polarization and electrochemical impedance measurements were used to evaluate the ability of compounds in reduction of the rate of corrosion. Quantum chemical calculations (QCCs) were also used to examine the corrosion inhibitive and the process related to the electrical and structural characteristics of the molecules acting as CIs.

The electrochemical measurements indicate that both Schiff bases acted as the efficient CIs of CS in 2 M HCl electrolyte. The adsorption of the Schiff base on the surface of the CS caused the corrosion to be inhibited. The change of Gibbs energies indicated that both physical and chemical interactions are involved in the adsorption of NNS and SNS on CS surfaces. The predicted QCCs of the CIs neutral and positively charged versions were well-aligned with those obtained by electrochemical experiments.

Using electrochemical experiments and quantum chemical modelings, two new Schiff bases, N-2-((2-nitrophenyl)thio)phenyl)-1-(pyrrole-2-yl)methanimine (NNS) and N-2-((2-nitrophenyl)thio)phenyl)-1-(thiophen-2-yl)methanimine (SNS), were evaluated as anti-corrosion agents for CS in 2 M HCl electrolyte. The DFT calculations were considered to compute the quantum chemical parameters of the inhibitors.

To address requirements and specifications of construction project, academics need to build a project classification model. In recent years, project success concept, particularly on large-scale construction projects, has been a controversial issue, especially in developing countries. Hence, in this paper, after introducing a sustainable success index (SSI), a novel method called “rough set approach” had been adopted to induce decision rules and to classify construction projects. The paper aims to discuss these issues.

At first, 20 effective success factors and 15 success criteria based on three pillars of sustainability of economy, society and environment had been categorized. The research data used for analysis had been collected from 26 large-scale construction projects in Iran and five other countries. After collecting data collection, observations had been analyzed and 51 decision rules were generated, and the projects were classified. Eventually, in order to evaluate the performance of the generated rules, confusion matrix was applied, and the model was validated.

The results of the present study show that rough set theory (RST) can be an effective and valuable tool for building expert systems. Practical applications of these results along with limitations and future research are described.

Perhaps for the first time, in the present study, a number of large-scale construction projects are classified based on SSI. Applying RST for building rule-based system and classifying projects in construction project area are novel attempts undertaken in this paper. The rules induced in this study can be applied to develop a sustainable success prediction model in the future studies.

This paper aims to study the effect of temperature on the process and kinetic parameters of the hydrogen evolution reaction of X80 under cathodic protection (CP) in 3.5% NaCl solution.

Potentiodynamic polarization combined with the hydrogen permeation test is used to analyze the hydrogen evolution reaction (HER) process and the rate-determining step for which is diagnosed through the electrochemical impedance spectrum method. Then, the influence of temperature on kinetic parameters of HER can be known from the results obtained by using the Iver-Pickering-Zamenzadeh model for data analysis.

The results show that the HER proceeds through Volmer–Tafel route with the Volmer reaction acting as the rate-controlling step; Increasing temperature gives a higher activity of the HER on X80, it also accelerates the hydrogen desorption and diffusion of hydrogen into the metal.

There exist few studies on the topic of how temperature affects the HER process. It is imperative to conduct a relevant study to give some instruction in cathodic protection system design and this paper fulfills this need.