Macroeconomic volatility and welfare loss under free-trade in two-country models

This paper investigates the interlinkage in the business cycles based on sunspot fluctuations of large-country economies in a free-trade equilibrium. We consider a two-country, two-good, two-factor general equilibrium model with Cobb-Douglastechnologies, sector-specific externalities and linear preferences. We also assume constant social returns in the investment good sector but decreasing social returns in the consumption good sector. We first identify the determinants of each country's accumulation pattern in autarky equilibrium, and second we show that some country's sunspot fluctuations may spread throughout the world once trade opens even if the other country has determinacy under autarky. We thus prove that under free-trade, globalization and market integration may have destabilizing effects on a country's competitive equilibrium. Finally, we characterize a configuration in which opening to international trade improves the stationary welfare at the world level but deteriorates the stationary welfare of the country which imports investment goods and exports consumption goods. We thus show that in opposition to the standard belief, international trade may not be beneficial to all trading partners in the long run. Moreover, we prove that for some country, international trade may have contrasted consequences as it may at the same time improve the stationary welfare and have a destabilizing effect.Two-country general equilibrium model, free-trade, local indeterminacy, sunspot fluctuations, capital intensities, decreasing social retur

Predictability of conversation partners

Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information theoretic method to the spatiotemporal data of cell-phone locations, [C. Song et al. Science 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one's conversation partners is defined as the degree to which one's next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to some extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual's predictability is correlated with the position in the static social network derived from the data. Individuals confined in a community - in the sense of an abundance of surrounding triangles - tend to have low predictability, and those bridging different communities tend to have high predictability.Comment: 38 pages, 19 figure

Macroeconomic volatility and welfare loss under free-trade in two-country models

This paper investigates the interlinkage in the business cycles based on sunspot fluctuations of large-country economies in a free-trade equilibrium. We consider a two-country, two-good, two-factor general equilibrium model with Cobb-Douglastechnologies, sector-specific externalities and linear preferences. We also assume constant social returns in the investment good sector but decreasing social returns in the consumption good sector. We first identify the determinants of each country's accumulation pattern in autarky equilibrium, and second we show that some country's sunspot fluctuations may spread throughout the world once trade opens even if the other country has determinacy under autarky. We thus prove that under free-trade, globalization and market integration may have destabilizing effects on a country's competitive equilibrium. Finally, we characterize a configuration in which opening to international trade improves the stationary welfare at the world level but deteriorates the stationary welfare of the country which imports investment goods and exports consumption goods. We thus show that in opposition to the standard belief, international trade may not be beneficial to all trading partners in the long run. Moreover, we prove that for some country, international trade may have contrasted consequences as it may at the same time improve the stationary welfare and have a destabilizing effect

Deep Multi-Agent Reinforcement Learning using DNN-Weight Evolution to Optimize Supply Chain Performance

To develop a supply chain management (SCM) system that performs optimally for both each entity in the chain and the entire chain, a multi-agent reinforcement learning (MARL) technique has been developed. To solve two problems of the MARL for SCM (building a Markov decision processes for a supply chain and avoiding learning stagnation in a way similar to the prisoner\u27s dilemma ), a learning management method with deep-neural-network (DNN)-weight evolution (LM-DWE) has been developed. By using a beer distribution game (BDG) as an example of a supply chain, experiments with a four-agent system were performed. Consequently, the LM-DWE successfully solved the above two problems and achieved 80.0% lower total cost than expert players of the BDG

Individual differences in environmental sensitivity: associations between cognitive emotion regulation and mental health

IntroductionEnvironmental sensitivity is defined as the ability to perceive and process internal and external information. Previous studies have suggested that mental health-related factors differ by sensitivity level. This study aimed to investigate whether environmental sensitivity moderates the associations between cognitive emotion regulation strategies (e.g., rumination and blaming others) and mental health.Materials and methodsIn this three-wave longitudinal study, participants (N = 1,233, 585, and 349 at Times 1, 2, and 3, respectively) completed the Cognitive Emotion Regulation Questionnaire-short and Kessler 10 scale at all the measurement points as well as the 10-item version of the Highly Sensitive Person scale and some covariates only at Time 1.ResultsLatent growth model analyses indicated that the blaming others strategy had contrastive effects on changes in mental health by sensitivity level; the increase in refocusing on planning was associated with improved mental health over time only for highly sensitive individuals; and the rumination and catastrophizing strategies were the most important risk factors for mental health problems, although their effects differed slightly by sensitivity level.ConclusionThe associations between some of the cognitive strategies and mental health differ by environmental sensitivity level. Future investigations based on individual differences in sensitivity could provide innovative insights into practices

Sensor-based Knowledge Discovery from a Large Quantity of Situational Variables

A new methodology called “sensor-based knowledge discovery”, which utilizes wearable sensors and statistical analysis, is proposed and evaluated. This methodology facilitates identifying new knowledge that can improve business outcome. It utilizes wearable sensors to unobtrusively capture people’s location, motion, and social interaction with others. The captured data is converted into multi-dimensional situational variables and then statistically analyzed to deliver a “rule set,” which forms the basis of new knowledge related to business outcome. The methodology was evaluated through a case study at a retail store. A hypothetical rule, that is, a particular area (a so-called “hot spot”) in the store where employee’s presence correlates with average sales per customer, was identified. Based on the identified rule, a measure to concentrate employees in that area was initiated. Consequently, increasing employees’ presence (“staying time”) in the hot spot by 70% increased average sales per customer by 15%. This result demonstrates the effectiveness of the methodology; namely, the new sensor-based knowledge discovery can improve actual business performance

Combination of violet light irradiation and collagenase treatments in a rabbit model of keratoconus

PurposeWe evaluated the use of collagenase treatment to generate a rabbit model of keratoconus and the impact of violet light (VL) irradiation on the disease model in six Japanese White rabbits.MethodsAfter epithelial debridement, the collagenase group was treated with a collagenase type II solution for 30 min; the control group was treated with a solution without collagenase. Three rabbits also underwent VL irradiation (375 nm, irradiance 310 μW/cm2) for 3 h daily for 7 days after topical collagenase application. Slit-lamp microscopy results, steep keratometry (Ks), corneal astigmatism, central corneal thickness, and axial length were examined before and after the procedure. The corneas were obtained on day 7 for biomechanical evaluation.ResultsA significant increase in Ks and corneal astigmatism was observed in the collagenase and VL irradiation groups compared with the control group on day 7. No significant difference was found in the change in corneal thickness between the groups. The elastic modulus at 3, 5, and 10% strain was significantly lower in the collagenase group than in the control group. There was no significant difference in the elastic modulus at any level of strain between the collagenase and VL irradiation groups. The average axial length at day 7 was significantly longer in the collagenase and VL irradiation groups than in the control group. Collagenase treatment induced a model of keratoconus by steepening the keratometric and astigmatic values. There was no significant difference in the observed elastic behavior of normal and ectatic corneas under physiologically relevant stress levels.ConclusionVL irradiation did not cause regression of corneal steepening in a collagenase-induced model during short-term observation

Life cycle assessment of hydrogenated biodiesel production from waste cooking oil using the catalytic cracking and hydrogenation method.

There is a worldwide trend towards stricter control of diesel exhaust emissions, however presently, there are technical impediments to the use of FAME (fatty acid methyl esters)-type biodiesel fuel (BDF). Although hydrogenated biodiesel (HBD) is anticipated as a new diesel fuel, the environmental performance of HBD and its utilization system have not been adequately clarified. Especially when waste cooking oil is used as feedstock, not only biofuel production but also the treatment of waste cooking oil is an important function for society. A life cycle assessment (LCA), including uncertainty analysis, was conducted to determine the environmental benefits (global warming, fossil fuel consumption, urban air pollution, and acidification) of HBD produced from waste cooking oil via catalytic cracking and hydrogenation, compared with fossil-derived diesel fuel or FAME-type BDF. Combined functional unit including "treatment of waste cooking oil" and "running diesel vehicle for household waste collection" was established in the context of Kyoto city, Japan. The calculation utilized characterization, damage, and integration factors identified by LIME2, which was based on an endpoint modeling method. The results show that if diesel vehicles that comply with the new Japanese long-term emissions gas standard are commonly used in the future, the benefit of FAME-type BDF will be relatively limited. Furthermore, the scenario that introduced HBD was most effective in reducing total environmental impact, meaning that a shift from FAME-type BDF to HBD would be more beneficial