Optimal Rating Design

We study the design of optimal rating systems in the presence of adverse selection and moral hazard. Buyers and sellers interact in a competitive market where goods are vertically differentiated according to their qualities. Sellers differ in their cost of quality provision, which is private information to them. An intermediary observes sellers' quality and chooses a rating system, i.e., a signal of quality for buyers, in order to incentivize sellers to produce high-quality goods. We provide a full characterization of the set of payoffs and qualities that can arise in equilibrium under an arbitrary rating system. We use this characterization to analyze Pareto optimal rating systems when seller's quality choice is deterministic and random

The effects of uncertainty of available information on investors' behaviors on herding formation

During the past century, there were different events where herding behavior created market turbulence and many investors were hurt, significantly. In this paper, we perform a survey to investigate investors’ behavior on creating herding behavior when they face with various levels of uncertainty on available information on the market. The survey designs a questionnaire, distributes it among some investors, and analyzes the results. The findings of our survey indicate that when there is a high level of uncertainty on publicly disclosed information, most investors assign more weights on confidential information or make no decision. In the event the uncertainty is on moderate level, investors rely more on publicly announced news and follow others’ behaviors. Finally, when the level of uncertainty is low, most investors depend on public information but this uncertainty creates less herding behavior compared with the previous case. The study also indicates that those investors who are normally making their decision with high inertia are not influenced by herding behavior

Experimental Study on a Novel Foaming Formula for CO2 Foam Flooding

This research developed a viable and economical foaming formula (AOS/AVS/N70K-T) which is capable of creating ample and robust CO2 foams. Its foaming ability and displacement performance in a porous medium were investigated and compared with the two conventional formulations (AOS alone and AOS/HPAM). The results showed that the proposed formula could significantly improve the foam stability without greatly affecting the foaming ability, with a salinity level of 20,000 ppm and a temperature of 323 K. Furthermore, AOS/AVS/N70K-T foams exhibited thickening advantages over the other formulations, especially where the foam quality was located around the transition zone. This novel formulation also showed remarkable blocking ability in the resistance factor (RF) test, which was attributed to the pronounced synergy between AVS and N70K-T. Last but not the least, it was found that the tertiary oil recovery of the CO2 foams induced by AOS/AVS/N70K-T was 12.5% higher than that of AOS foams and 6.8% higher than that of AOS/HPAM foams at 323 K and 1500 psi, thus indicating its huge enhanced oil recovery (EOR) potential. Through systematic research, it is felt that the novel foaming formulation might be considered as a promising and practical candidate for CO2 foam flooding in the future

Tight gas sands permeability estimation from mercury injection capillary pressure and nuclear magnetic resonance data

There are several methods to estimate permeability from pore throat sizes and NMR T2 relaxation time. Although most of the methods are well-established and work well for conventional reservoirs they fail to estimate permeability for tight gas sands. The aim of this study was to establish relationships between permeability and pore throat sizes, derived from mercury injection analysis, and NMR T2 relaxation time. Regression analysis was used to achieve a set of relationships between dry gas permeability, porosity and pore throat sizes for 50 tight gas sand samples. Unlike for normal sandstone, pore throat radii corresponding to a mercury saturation of 10% (r10) is the best permeability predictor for tight gas sands. For tight gas sands, NMR T2 relaxation spectra fall on the shorter values corresponding to the smaller pores. This is because pore spaces are significantly reduced both in size and volume due to extensive compaction and cementation. This study shows that using NMR T2peak and multi-regression analysis, permeability can be estimated with high accuracy even in rocks with substantially constricted pore throats

An experimental study of combined foam/surfactant polymer (SP) flooding for carbone dioxide-enhanced oil recovery (CO2-EOR)

To better address the issue of viscous fingering and gravity segregation confronted in CO2 flooding, a novel EOR method which coupled the SP flooding with the CO2 foam flooding was presented. Its displacement performance was systematically evaluated and compared with the other two injections modes (i.e. direct foam flooding and CO2/SP flooding) which applied the same amount of the gas and chemicals as the proposed mode. It had been found, if the injection pressure enabled the oil/CO2 miscibility to occur, the foam/SP flooding was endowed with the highest blockage and lowest water cut. Moreover, its oil recovery factor was 5.8% and 12.6% greater than that of direct foam CO2/SP flooding respectively; on the other hand, if the injection pressure was below the minimum miscibility pressure (MMP), the direct foam flooding and the SP flooding displayed comparable water cut and oil recovery factor. Although the foam/SP flooding still recovered the most crude oil, it was only 3.7% and 6.8% higher than that of the direct foam and SP flooding respectively, indicating the less evident displacement advantage. It was believed that the proposed method possessed huge EOR potential, especially in the reservoir whose pressure was well above the MMP

New Methods in Treatment of Renal failure in Patients with Multiple Myeloma: A Review with Immunological Approach.

Multiple myeloma (MM), as one of a variety of autoimmune diseases, affects the immune system and, on the other hand, is considered to be a hematologic impairment. One of the most common and important complications of MM is renal impairment (RI), which is associated with an increase in serum Cr levels. Although RI is one of the major complications of MM, the routine therapies for MM patients practically lack acceptable efficacy for the improvement of RI patients, and as a result, RI remains a deadly disease with high mortality rate and very bad prognosis; therefore, new treatments have been proposed for the improvement of nephropathy in patients with MM, and extensive research is ongoing in various phases, including clinical trials. Attempts were made in this study to review common and advanced treatments (immunotherapy, cell therapy, new therapies based on genetic engineering) in these patients and to consider this disease from an immunological viewpoint

The Relationship Between Individual Stock Trading And Returns: The Case Of An Emerging Market

This research investigates the relationship between stock trading of individual investors and returns in short horizon in an emerging market. The results indicate that the individuals would like to invest in stocks after declining in the preceding month prices and they would like to sell after increasing in prices. Moreover, we find that there are positive abnormal returns in the month after high buying by individuals and there are negative abnormal returns following high individuals selling. The result is consistent with the literature that the individuals play roles of liquidity providers because they can meet the institutional need of immediacy

Computerized cognitive training for improving cochlear-implanted children's working memory and language skills

Abstract Sensory deprivation, including hearing loss, can affect different aspects of a person’s life. Studies on children with hearing impairment have shown that such patients, especially those with cochlear implants (CIs), suffer from cognitive impairments, such as working memory problems and poor language skills. The present study aimed to examine the efficacy of cognitive computer training in improving working memory and language skills in children with a CI.This research was a quasi-experimental study with a pre-test-post-test design and a control group. Fifty-one children with a CI aged 6-12 years were recruited through convenience sampling and randomly assigned to the control and treatment groups. The Wechsler Working Memory Subtest and the Test of Language Development (TOLD) were used to evaluate children’s working memory and language skills pre- and post-treatment. The treatment group attended twenty 50-60-minute cognitive computer training sessions three times a week.Sina-Working Memory Training was used to provide the treatment group with working memory training, whereas no intervention was provided to the control group. Univariate and multivariate analysesof covariance were used to analyze data.The results demonstrated the efficacy of cognitive computer training in improving the performance of cochlear-implanted children’s working memory (auditory and visual-spatial) (P < 0.01). The results also pointed to improved performance in sentence imitation (P < 0.01), word discrimination (P < 0.01), and phonemic analysissubtests (P < 0.01).Overall, the findings indicated that cognitive computer training might improve working memory and language skills for children with CI. Therefore, the development and execution of such programs for children with CIs seem to improve their cognitive functions, such as working memory and language skills

The Impact of Twitter Sentiments on Stock Market Trends

The Web is a vast virtual space where people can share their opinions, impacting all aspects of life and having implications for marketing and communication. The most up-to-date and comprehensive information can be found on social media because of how widespread and straightforward it is to post a message. Proportionately, they are regarded as a valuable resource for making precise market predictions. In particular, Twitter has developed into a potent tool for understanding user sentiment. This article examines how well tweets can influence stock symbol trends. We analyze the volume, sentiment, and mentions of the top five stock symbols in the S&P 500 index on Twitter over three months. Long Short-Term Memory, Bernoulli Na\"ive Bayes, and Random Forest were the three algorithms implemented in this process. Our study revealed a significant correlation between stock prices and Twitter sentiment