Development of incremental deep drawing process

This paper deals with development of an incremental deep drawing process. On a newly developed incremental deep drawing set-up, the aluminium sheets are formed; the forming is carried out by deep-drawing the blank as in the conventional method but incrementally. Fractures at the punch or die corner in the blank may or may not occur depending on the conditions; the process parameters involved are punch size, punch corner radius, increment in punch displacement, blank holding force or pressure, etc. It is thus shown that different shapes are formed by one set of common tools. It is thereby confirmed that incremental deep drawing is possible without using a particular tool set for a particular shape.     

A Study of Polymer Electrolyte Fuel Cells by the Measurement of AC Impedance,Current Interrupt,and Dew Points: 2. Effect of Cell Temperature

The effect of cell temperature on the performance of a polymer electrolyte fuel cell was examined in the present study. Measurements using the current interrupt and AC impedance methods showed that membrane resistance increased as the cell temperature was reduced. The charge transfer resistance, determined by the AC impedance method, also increased with decreasing cell temperature. The results of electrochemical analysis showed that the temperature of the cell strongly affected the performance of the membrane–electrode assembly in the cell. In addition, the water balance calculated from dew points of fuel gases changed with cell temperature. At a cell temperature of 80 °C, ca. 80% of the water generated on the cathode passed through the membrane to the anode, while at a cell temperature of 40 °C, only ca. 20% of the water on the cathode passed through the membrane to the anode.     

Another approach to asymptotic model matching problem for nonlinear systems

This paper deals with the asymptotic model matching problem for square nonlinear systems. This problem has been studied by Di Benedetto and Grizzle via geometric approach. We adopt another approach. It is based on an idea that this problem is similar to the nonlinear servomechanism (output regulation) problem. By means of slight modification of the problem statement, a sufficient condition is given. It is described as the solvability of a certain partial differential equation. Its reduction and approximation methods are proposed. © 1998 John Wiley & Sons, Ltd.     

Airborne endotoxin concentrations in indoor and outdoor particulate matter and their predictors in an urban city

Endotoxins are an important biological component of particulate matter and have been associated with adverse effects on human health. There have been some recent studies on airborne endotoxin concentrations. We collected fine (PM_2.5) and coarse (PM_10‐2.5) particulate matter twice on weekdays and weekends each for 48 hour, inside and outside 55 homes in an urban city in Japan. Endotoxin concentrations in both fractions were measured using the kinetic Limulus Amebocyte Lysate assay. The relationships between endotoxin concentrations and household characteristics were evaluated for each fraction. Both indoor and outdoor endotoxin concentrations were higher in PM_2.5 than in PM_10‐2.5. In both PM_2.5 and PM_10‐2.5, indoor endotoxin concentrations were higher than outdoor concentrations, and the indoor endotoxin concentrations significantly correlated with outdoor concentrations in each fraction (R²=0.458 and 0.198, respectively). Indoor endotoxin concentrations in PM_2.5 were significantly higher in homes with tatami or carpet flooring and in homes with pets, and lower in homes that used air purifiers. Indoor endotoxin concentrations in PM_10‐2.5 were significantly higher in homes with two or more children and homes with tatami or carpet flooring. These results showed that the indoor endotoxin concentrations were associated with the household characteristics in addition to outdoor endotoxin concentrations.     

Computed tomography reconstruction from two transmission measurements for iodine-marked cancer detection

The authors invented the transXend detector, which measures X-rays as electric currents, and then gives the energy distribution of the X-rays after an unfolding process. In a previous paper, it was shown that the material thickness distributions can be estimated with the transXend detector by using reference points plotted from the electric current ratios, such as the I ₂/I ₁ ? I ₃/I ₁ graph, where I_i denotes the electric current measured by the i-th segment of the transXend detector. In this paper, the tomographic images of iodine, aluminum, and the acrylic those surround the other two materials are reconstructed from their material thickness distributions, which are estimated from two X-ray incidence directions. The X-ray event ratios are also used to estimate the material thickness distributions.     

Low-dose exposure energy-resolved X-ray computed tomography using a contrast agent with a high-energy K-edge

X-ray computed tomography (CT) with iodine contrast agent is widely employed to locate cancers. However, this method has shortcomings such as high-radiation dose exposure, iodine side effects, and a beam hardening effect. We have been working on the energy-resolved CT measurement method using a novel X-ray detection system, the “transXend” detector, which measures X-rays as electric currents and gives the energy distribution of incident X-rays after analysis. In the present study, we propose a method for low-dose exposure CT that involves the combination of the energy-resolved CT method, which is free from the beam hardening effect, and a harmless contrast agent with high-energy K-edge absorption, such as gold nanoparticles expected as a future contrast agent. Comparisons of radiation dose exposures as functions of aluminum filter thickness at the exit aperture of an X-ray tube and the K-edge energies of contrast agents are described.     

Does Density Aggravate the COVID-19 Pandemic?

Abstract

Problem, research strategy, and findings: The impact of density on emerging highly contagious infectious diseases has rarely been studied. In theory, dense areas lead to more face-to-face interaction among residents, which makes them potential hotspots for the rapid spread of pandemics. On the other hand, dense areas may have better access to health care facilities and greater implementation of social distancing policies and practices. The current COVID-19 pandemic is a perfect case study to investigate these relationships. Our study uses structural equation modeling to account for both direct and indirect impacts of density on the COVID-19 infection and mortality rates for 913?U.S. metropolitan counties, controlling for key confounding factors. We find metropolitan population to be one of the most significant predictors of infection rates; larger metropolitan areas have higher infection and higher mortality rates. We also find that after controlling for metropolitan population, county density is not significantly related to the infection rate, possibly due to more adherence to social distancing guidelines. However, counties with higher densities have significantly lower virus-related mortality rates than do counties with lower densities, possibly due to superior health care systems.

Takeaway for practice: These findings suggest that connectivity matters more than density in the spread of the COVID-19 pandemic. Large metropolitan areas with a higher number of counties tightly linked together through economic, social, and commuting relationships are the most vulnerable to the pandemic outbreaks. They are more likely to exchange tourists and businesspeople within themselves and with other parts, thus increasing the risk of cross-border infections. Our study concludes with a key recommendation that planners continue to advocate dense development for a host of reasons, including lower death rates due to infectious diseases like COVID-19.     

Game theory methodology for optimizing retailers’ pricing and shelf-space allocation decisions on competing substitutable products

This paper examines the influence of competition among supply chain partners on product demand. A power law demand function that depends on product pricing and shelf-space allocation (SSA) is used. The exponents in the power law are given by the elasticities of demand. In order to achieve the optimal pricing and SSA strategies in the presence of competition, game-theory-based methodologies—Cournot and Stackelberg games—are employed. For each type of game, a Nash equilibrium is achieved by optimizing the profit as a function of demand and price. A case study is presented to demonstrate the potential of this methodology. The results of this study indicate (1) how to achieve optimal pricing and SSA strategies, (2) how manufacturers can influence demand for a product, (3) that both prices and profits decrease using the Stackelberg game as compared with the Cournot game, and (4) that coordination beyond simple knowledge of price would be beneficial for improving overall profits.     

Designing a cellular manufacturing system considering decision style,skill and job security by NSGA-II and response surface methodology

Cell formation is a traditional problem in cellular manufacturing systems that concerns the allocation of parts, operators and machines to the cells. This paper presents a new mathematical programming model for cell formation in which operators’ personality and decision-making styles, skill in working with machines, and also job security are incorporated simultaneously. The model involves the following five objectives: (1) minimising costs of adding new machines to and removing machines from the cells at the beginning of each period, (2) minimising total cost of material handling, (3) maximising job security, (4) minimising inconsistency of operators’ decision styles in cells and (5) minimising cost of suitable skill. On account of the NP-hard nature of the proposed model, NSGA-II as a powerful meta-heuristic approach is used for solving large-sized problems. Furthermore, response surface methodology (RSM) is used for tuning the parameters. Lastly, MOPSO and two scalarization methods are employed for validation of the results obtained. To the best of our knowledge, this is the first study that presents a multi-objective mathematical model for cell formation problem considering operators’ personality and skill, addition and removal of machines and job security.