Exit and Voice in a Marriage Market

In this paper, we present a model in which agents choose voice, exit, or stay options when their marital condition becomes bad. The voice option can be interpreted as a spouses e¤ort or investment in the household to resolve his/her dissatisfaction and improve the marital condition. If a spouse hopes to divorce, he/she chooses the exitoption. If a spouse does not hope to express his/her opinion and divorce, he/she chooses the stayoption. We focus on the role of exitand voicein a marriage and investigate the e¤ects of a divorce law that is based on fault or no-fault on divorce rates. Our study shows that divorce rates tend to be too high under a unilateral divorce law in the non-transferable utility case. On the other hand, mutual-consent divorce law generates multiple equilibria, and divorce rates are then ine ¢ cient even in the transferable utility case. In this multiple equilibrium case

The Effects of Business Strategy on Economic Evaluation Techniques of Capital Investment

This paper explains firms’ adoption of economic evaluation techniques according to differences in their business strategy and their business environment using mail survey data. Many recent studies focus only on the discount cash flow (DCF) methods, while our research examines the factors determining the use of non-DCF methods as well as DCF methods, and shows the rationality of their use. We discover that the use of non-DCF methods, such as payback method and accounting rate of return, is rational when the use of DCF methods is not valid. We find that business environment characteristics, such as (1) the complexity of the environment, (2) uncertainty, and (3) automation of the production line, affect the choice of the evaluation technique. Furthermore, we find that whether a firm’s strategic type is an analyzer or not affects the adoption of the economic evaluation technique

The Consistency Between Investment Management Process and Business Strategy

This paper examines the management process for each strategic type of firm (namely, Defenders, Prospectors, Analyzers, and Reactors) as a new way of analyzing capital budgeting from a managerial accounting perspective. Using a 2009 survey of Japanese manufacturing firms, we reveal the following. To start with, Defenders seldom search for new investment projects because they establish a stable status in a limited operation domain. Therefore, the principal purpose of capital investment in this strategic type is to improve cost competitiveness. As a result, Defenders develop the investment project in their own way, and then evaluate profitability thoroughly following implementation. In contrast, Prospectors continuously search for market opportunities, and evaluate and select projects in order to pioneer new product markets and profit opportunities. Thus, the main purpose of capital investment in this strategic type is to produce new products. Consequently, Prospectors emphasize profitability and timing in the development phase, and then carefully compare the alternative projects available. Finally, Analyzers carefully deliberate and decide upon the optimum timing of investment in order to seize upon market opportunities using their existing technology. As a result, this strategic type does not aggressively pursue capital investment

Matching Capital Investment Management with Business Strategy

Most competitive strategic theory employs the assumption that firms should undertake appropriate management actions for each particular strategy. Studies in managerial accounting also use this to examine how the practice of business management fits the firm’s strategy. This paper clarifies how the consistency between a firm’s business strategy and investment management efforts affects business performance. We employ a mail survey of Japanese manufacturing firms conducted in 2009 to identify Miles–Snow strategic types among respondent firms and test hypotheses concerning the effects of the interaction between investment management and firm strategic tendencies on firm performance, as measured by the return on assets. We find that investment management for Defender-type firms corresponds with traditional managerial accounting methods such as planning and control, while that for Prospector-type firms does not

Dual phase regulation of experimental allergic encephalomyelitis by platelet-activating factor

Experimental allergic encephalomyelitis (EAE) serves as a model for multiple sclerosis and is considered to be a CD4+ Th1 cell–mediated autoimmune disease. To investigate the role of platelet-activating factor (PAF) in this disease, PAF receptor (PAFR) KO (PAFR-KO) and wild-type (WT) mice, on a C57BL/6 genetic background, were immunized with myelin oligodendrocyte glycoprotein 35–55. The levels of PAF production and PAFR mRNA expression in the spinal cord (SC) correlated with the EAE symptoms. PAFR-KO mice showed lower incidence and less severe symptoms in the chronic phase of EAE than WT mice. However, no difference was observed in T cell proliferation, Th1-cytokine production, or titer of IgG2a between both genotypes. Before onset, as revealed by microarray analysis, mRNAs of inflammatory mediators and their receptors—including IL-6 and CC chemokine receptor 2—were down-regulated in the SC of PAFR-KO mice compared with WT mice. Moreover, in the chronic phase, the severity of inflammation and demyelination in the SC was substantially reduced in PAFR-KO mice. PAFR-KO macrophages reduced phagocytic activity and subsequent production of TNF-α. These results suggest that PAF plays a dual role in EAE pathology in the induction and chronic phases through the T cell–independent pathways

New Particle Identification Approach with Convolutional Neural Networks in GAPS

The General Antiparticle Spectrometer (GAPS) is a balloon-borne experiment that aims to measure low-energy cosmic-ray antiparticles. GAPS has developed a new antiparticle identification technique based on exotic atom formation caused by incident particles, which is achieved by ten layers of Si(Li) detector tracker in GAPS. The conventional analysis uses the physical quantities of the reconstructed incident and secondary particles. In parallel with this, we have developed a complementary approach based on deep neural networks. This paper presents a new convolutional neural network (CNN) technique. A three-dimensional CNN takes energy depositions as three-dimensional inputs and learns to identify their positional/energy correlations. The combination of the physical quantities and the CNN technique is also investigated. The findings show that the new technique outperforms existing machine learning-based methods in particle identification.Comment: 7 pages, 10 figure

Comment on: Nathan DM, Buse JB, Davidson MB et al. (2006) Management of hyperglycaemia in type 2 diabetes: a consensus algorithm for the initiation and adjustment of therapy. A consensus statement from the American Diabetes Association and the European Association for the Study of Diabetes.

金沢大学大学院医学系研究科環境社会医