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This study aims to investigate the effects of ball–material ratio on the properties of mixed powders and Cu-Bi self-lubricating alloy materials.

Cu-Bi mixed powder was ball milled at different ball–material ratios, and the preparation of Cu-Bi alloy materials was achieved through powder metallurgy technology. Scanning electron microscopy, X-ray diffraction and Raman spectroscopy were conducted to study the microstructure and phase composition of the mixed powder. The apparent density and flow characteristics of mixed powders were investigated using a Hall flowmeter. Tests on the crushing strength, impact toughness and tribological properties of self-lubricating alloy materials were conducted using a universal electronic testing machine, 300 J pendulum impact testing machine and M200 ring-block tribometer, respectively.

With the increase in ball–material ratio, the spherical copper matrix particles in the mixed powder became lamellar, the mechanical properties of the material gradually reduced, the friction coefficient of the material first decreased and then stabilized and the wear rate decreased initially and then increased. The increase in the ball–material ratio resulted in the fine network distribution of the Bi phase in the copper alloy matrix, which benefitted its enrichment on the worn surface for the formation a lubricating film and improvement of the material’s tribological performance. However, a large ball–material ratio can excessively weaken the mechanical properties of the material and reduce its wear resistance.

The effects of ball–material ratio on Cu-Bi mixed powder and material properties were clarified. This work provides a reference for the mechanical alloying process and its engineering applications.

The purpose of the study is to optimize the blending ratio of Arecanut and cotton fibers to create yarn with the best quality for various applications, particularly home furnishings. The study aims to determine the effect of different blend ratios on the physical and mechanical properties of the yarn.

The study involves blending Arecanut and cotton fibers in various ratios (90:10, 75:25, 50:50, 25:75 and 10:90) at two different yarn counts (10/1 and 5/1). Various physical and mechanical properties of the blended yarn are analyzed, including unevenness, coefficient of mass variation (cvm%), imperfection, hairiness, breaking strength, elongation, tenacity and breaking work.

The research findings suggest that the blend ratio of 10:90 (10% cotton and 90% Arecanut fiber) produced the best results in terms of physical and mechanical properties for both yarn counts. This blend ratio resulted in reduced unevenness, cvm% and imperfection, while also exhibiting good mechanical properties such as breaking strength, elongation, tenacity and breaking work. The blend with a higher concentration of cotton generally showed better properties due to the coarseness of Arecanut fiber. As the goal of the study was to determine the best blend ratio that included the most Arecanut fiber based on its physical and mechanical properties, which is suitable for home furnishing applications, 75:25 Areca cotton blend ratio of yarn count 5/1 proved to be the best.

The study acknowledges that Arecanut fiber must be blended with other commercially used fibers like cotton due to its coarseness. While the study provides insights into optimizing blend ratios for home furnishings and packaging, further research may be needed to make the material suitable for clothing applications.

The research has practical implications for industries interested in utilizing Arecanut and cotton blends for various applications, such as home furnishings and packaging materials. It suggests that specific blend ratios can result in yarn with desirable properties for these purposes.

The study mentions that the increased use of Arecanut fibers can benefit the growers of Arecanut, potentially providing economic opportunities for communities engaged in Arecanut farming.

The research explores the utilization of Arecanut fibers, an underutilized resource, in combination with cotton to create sustainable yarn. It assesses various blend ratios and their impact on yarn properties, contributing to the understanding of eco-friendly textile materials.

Using the next-day and next-week returns of stocks in the Korean market, we examine the association of option volume ratios – i.e. the option-to-stock (O/S) ratio, which is the total volume of put options and call options scaled by total underlying equity volume, and the put-call (P/C) ratio, which is the put volume scaled by total put and call volume – with future returns. We find that O/S ratios are positively related to future returns, but P/C ratios have no significant association with returns. We calculate individual, institutional, and foreign investors’ option ratios to determine which ratios are significantly related to future returns and find that, for all investors, higher O/S ratios predict higher future returns. The predictability of P/C depends on the investors: institutional and individual investors’ P/C ratios are not related to returns, but foreign P/C predicts negative next-day returns. For net-buying O/S ratios, institutional net-buying put-to-stock ratios consistently predict negative future returns. Institutions’ buying and selling put ratios also predict returns. In short, institutional put-to-share ratios predict future returns when we use various option ratios, but individual option ratios do not.

Why Ratios? The need for ratios rests upon the fact that absolute figures by themselves tell one very little about the performance of an organisation. The fact that a company made £1 million pre‐tax profit in its last financial year is no indication of its performance. If it had to deploy £1,000 millions of funds to achieve that profit then its performance was abysmally low. If it only employed £2 millions its performance was very good. In one sense then ratio analysis is concerned with expressing relationships between inputs and outputs, such as the capital required to support an activity and the profit earned from that activity; the sales achieved per square foot of sales space occupied; the cost per ton‐mile of delivering goods; and the way in which these different aspects relate to each other and to overall performance. In another sense they are concerned with relationships between aspects of a business which are crucial for its success, e.g. the relationship between short‐term assets and short term liabilities because it reflects the ability of the business to meet its obligations to creditors.

The application of factor analysis to the area of financial ratio analysis was pioneered by Pinches, Mingo, and Caruthers (1973) in a study of U.S. industrial firms. During the last two decades numerous studies have applied the technique as a means of eliminating redundancy among financial ratios and/or reducing the number of ratios selected as a basis for further investigation to a limited but crucial subset. It is observed that all studies reported were on the manufacturing and retailing sectors. The international commercial airline sector was chosen as the subject of the present research in an attempt to study the factor groupings in a sector whose financial characteristics differ from manufacturing or retailing. Results show that factor categorization reflects the sector's financial characteristics. The study also draws conclusions on some observed differences between the empirical and theoretical ratio classification observed in the literature. The study lends support to the conclusion that factor analysis provides a useful means by which to develop and test the theoretical structure and grouping of financial ratios.

This paper seeks to model and evaluate the comparative operating efficiency of banks using a non‐parametric methodology known as the data envelopment analysis (DEA). The paper adopts a modified version of DEA in which no inputs are specified. The only variables considered are the financial ratios. The results obtained suggest that the majority of banks investigated are fairly inefficient over the period 1991‐94. In addition to calculating efficiency scores for all banks in the sample, the study results revealed the composite reference set and their shadow prices, major determinants of banks’ relative performance, and the target financial ratios.

The purpose of this paper is to examine the impact of financial ratios on the financial performance of a chemical company: LyondellBasell Industries (LYB). Some selected ratios: current ratio (CR) and quick ratio (QR) represent the liquidity ratios, debt ratio (DR) and debt equity ratio (DTER) represent the leverage ratios, while operating profit margin (OPM) and net profit margin (NPM) represent the profitability ratios. LYB faced financial problems after its merger and the financial performance of the company shrank to negative due to the world financial crisis. However, this company has bounced back after a year and is now the world's third largest chemical company based on revenue.

The financial ratios were measured from 2004 to 2011, quarterly. A multiple regression model has been used and secondary data has been analyzed.

The results shows that CR, QR, DR and NPM have a positive relationship while DTER and OPM have a negative relationship with the company's financial performance. Among the six ratios, CR, DR and NPM show the highest significant impact on the company's performance.

This research paper contributed the result of the impact of financial ratios on the financial performance of a chemical company as the previous studies with this focus are hard to find and some of the sources are not specifically related to the topic.

The problem of cyclic variation has been an interesting area of research and has been investigated by many researchers. It is more severe in the case of two‐stroke engines compared with four‐stroke engines. One of the reasons for these cycle‐to‐cycle variations is the variations in the air‐fuel ratios of individual cycles and, if these values of individual cycle air‐fuel ratios are available by some means, they can be used for controlling the cyclic variations. The purpose of this paper is to find a technique to predict the air‐fuel ratio of the individual cycles and use the same for reducing cyclic variations.

In this work, a neuro‐fuzzy model was developed using MATLAB software to compute the air‐fuel ratio of the individual cycles based on the relationship between the air‐fuel ratio and the combustion parameters such as those indicating mean effective pressure (IMEP), crank angle occurrence of peak pressure, and angles of different percentages of heat releases. In‐cylinder pressure traces of 1,000 continuous cycles were measured using a Personal Computer (PC)‐based data acquisition system and an investigation was carried out. The readings were taken for two modes of operations, namely gasoline carburetion and electronic gasoline injection. The engine was loaded by an eddy current dynamometer. The air‐fuel ratio was varied from rich to lean by adjusting the fuel quantity in the carburetion mode and adjusting the pulse width (measure of quantity of fuel to be injected) in the injection mode, at constant throttle. The cyclic variation was identified by the variations in the peak pressures and IMEPs of the individual cycles. The stored data were given as input to the developed neuro‐fuzzy model and, using SIMULINK, the air‐fuel ratios of individual cycles were obtained. These predicted values are fed to the electronic control module (ECM) (meant for injecting the fuel) for refining the pulse width to get cyclic variations reduced.

Results show that cyclic variation increases when the mixture becomes lean. It was also found that cyclic variation in an injected engine was less in comparison with the carbureted engine, as the precise control of air‐fuel mixture was possible in the case of the injected engine.

The technique used in this work may be modified to give more precise pulse width by incorporating various other parameters like exhaust temperature, etc. Future research may be focused to incorporate this system in a moving vehicle to get more fuel efficiency and fewer emissions.

The design of vehicle and engine should be slightly modified to incorporate the ECM and various sensors.

The originality in this paper is that a new technique was developed to find the air‐fuel ratio of individual cycles. This will be useful for the engine manufacturers and for those researchers doing research on the engine side.

The purpose of this research is to evaluate the financial performance measures calculated and reported by the Economic Resource Service (ERS) from Agricultural Resource Management Survey (ARMS) data. The evaluation includes the calculation method and the underlying assumptions used in obtaining the reported values. Recommendations for improving the information reported are proposed to ERS.

The financial measures calculated and reported are compared with those recommended by the Farm Financial Standards Council (FFSC). The underlying assumptions are identified by analyzing the software code used in calculating the values reported. The values reported by ERS are duplicated and alternative methods for calculating the financial performance measures are considered. The values obtained from the various calculation methods are compared and contrasted.

Recommendations for ERS include: calculate and report the financial measures recommended by FFSC, note values that are imputed, periodically update and validate assumptions used in calculating imputed values, review its policy for flagging estimates as statistically unreliable, report medians and other select percentiles, and consider reporting the percent of farm businesses that have values within critical zones.

A total of four methods for calculating financial performance measures are compared and contrasted. These are the aggregate mean, sample mean, sample median, and percentage of farm businesses with values in critical zones.