Financial distress prediction using integrated Z-score and multilayer perceptron neural networks.

The COVID-19 pandemic led to a great deal of financial uncertainty in the stock market. An initial drop in March 2020 was followed by unexpected rapid growth over 2021. Therefore, financial risk forecasting continues to be a central issue in financial planning, dealing with new types of uncertainty. This paper presents a stock market forecasting model combining a multi-layer perceptron artificial neural network (MLP-ANN) with the traditional Altman Z-Score model. The contribution of the paper is presentation of a new hybrid enterprise crisis warning model combining Z-score and MLP-ANN models. The new hybrid default prediction model is demonstrated using Chinese data. The results of empirical analysis show that the average correct classification rate of thew hybrid neural network model (99.40%) is higher than that of the Altman Z-score model (86.54%) and of the pure neural network method (98.26%). Our model can provide early warning signals of a company's deteriorating financial situation to managers and other related personnel, investors and creditors, government regulators, financial institutions and analysts and others so that they can take timely measures to avoid losses.

Microbially influenced corrosion communities associated with fuel-grade ethanol environments.

Microbially influenced corrosion (MIC) is a costly problem that impacts hydrocarbon production and processing equipment, water distribution systems, ships, railcars, and other types of metallic infrastructure. In particular, MIC is known to cause considerable damage to hydrocarbon fuel infrastructure including production, transportation, and storage systems, often times with catastrophic environmental contamination results. As the production and use of alternative fuels such as fuel-grade ethanol (FGE) increase, it is important to consider MIC of engineered materials exposed to these "newer fuels" as they enter existing infrastructure. Reports of suspected MIC in systems handling FGE and water prompted an investigation of the microbial diversity associated with these environments. Small subunit ribosomal RNA gene pyrosequencing surveys indicate that acetic-acid-producing bacteria (Acetobacter spp. and Gluconacetobacter spp.) are prevalent in environments exposed to FGE and water. Other microbes previously implicated in corrosion, such as sulfate-reducing bacteria and methanogens, were also identified. In addition, acetic-acid-producing microbes and sulfate-reducing microbes were cultivated from sampled environments containing FGE and water. Results indicate that complex microbial communities form in these FGE environments and could cause significant MIC-related damage that may be difficult to control. How to better manage these microbial communities will be a defining aspect of improving mitigation of global infrastructure corrosion.

Cellular response of titanium and its alloys as implants.

The cellular response of osteocytes to commercially pure titanium (α) and its alloys (α + ß and ß) has been tested in a culture media, and the results have been supplemented by analyses from various techniques such as inductively coupled plasma atomic emission spectroscopic (ICP-AES) analysis, X-ray photoemission spectroscopy (XPS), scanning electron microscopy (SEM), metallography, and electrochemical measurements. These results have been correlated with respect to the presence of various alloying elements in these alloys to qualify them for human application. The newer ß alloys have been examined for their potential use as implants. These results serve as a preliminary baseline to characterize the best alloy system for a comprehensive long-term investigation.

Effect of povidone-iodine addition on the corrosion behavior of cp-Ti in normal saline.

The effect of various concentrations of povidone-iodine (PI) on the corrosion behavior of a commercially pure titanium alloy (Ti-1) has been investigated in normal saline solution to simulate the povidone-iodine addition in an oral environment. The open circuit potential, electrochemical impedance spectroscopy and potentiodynamic polarization measurements have been used to characterize the electrochemical phenomena occurring on the alloy surface. The open circuit potential values for Ti-1 in various concentrations of PI shift considerably towards noble direction as compared to pure normal saline. In the potentiodynamic polarization curve for Ti-1 in various solutions, the cathodic current density has increased for all concentrations of PI and the anodic current density has decreased. Only the 0.1% PI concentration is able to inhibit corrosion of Ti-1 in normal saline and the other higher concentrations studied, accelerate corrosion. The EIS data for Ti-1 in normal saline and in various concentrations of PI follows a one time constant circuit, suggesting the formation of a single passive film on Ti-1 which is not altered by the addition of PI to normal saline.

Rehabilitation settings after joint replacement: an application of multiattribute preference elicitation.

While advances in medical treatment and technologies have the potential to improve the delivery of health care, their use typically involves making multiple, complex decisions. Patients and their medical providers may share in the decision-making processes and balance a variety of criteria and/or attributes in the pursuit of improved health. This necessitates a stronger understanding of the role of human behavior in health care processes and presents a timely opportunity to use decision analysis tools to contribute to this important aspect of health care operations. This article reports on the application of multiattribute preference elicitation to identify postsurgical rehabilitation setting options for elective hip and knee replacement patients and their discharge planning team prior to placement in these settings. These preferences are analyzed to identify trends in emphases across patients and the discharge planning team, including a comparison with actual outcomes to determine the extent of congruence with each other, an important component of patient-centered care. Variances are identified in what patients and the discharge planning team expected and what actually happened. Reasons for these variances are discussed.