Dynamics of clustered opinions in complex networks

A simple model for simulating tug of war game as varying the player number in a team is discussed to identify the slow pace of fast change. This model shows that a large number of information sources leads slow change for the system. Also, we introduce an opinion diffusion model including the effect of a high degree of clustering. This model shows that the de facto standard and lock-in effect, well-known phenomena in economics and business management, can be explained by the network clusters.Comment: 11 pages, 2 figure

Primary Candida guilliermondii Infection of the Knee in a Patient without Predisposing Factors

Isolated primary candidal infection of joint is extremely rare, with only a few reported cases. It occurs as a result of accidental implantations of fungus during traumatic procedures, such as surgery, and is usually reported in patients with predisposing factors such as immunosuppression, malignancy, and drug abuse. If left untreated, irreversible deformity and pain with severe osteoarticular destruction occur. Thus, early diagnosis and treatment are important. This paper presents a case of 72-year-old man with primary C. guilliermondii infection of knee joint without predisposing factors and previous traumatic procedures, who was misdiagnosed with advanced degenerative osteoarthritis. Our case is the second case of primary C. guilliermondii arthritis of knee to be reported in the English-language literature and the first to be successfully treated with total knee arthroplasty following IV amphotericin B and oral fluconazole. Primary candidal infection of joint is generally asymptomatic or involves only mild pain and swelling in the affected knee. Thus, although the majority of knee joint infections are of a pyogenic or tuberculous origin, if a patient complains of mild pain and swelling in the knee and has mild signs of infection, the possibility of fungal infection should be considered

High Temperature Deformation Behavior of 8090 Al-Li Alloy

High temperature deformation behavior, especially the superplasticity of an 8090 Al-Li alloy, was studied within the recent framework of the internal variable theory of structural superplasticity. In this study, a series of load relaxation tests were conducted at various temperatures ranging from 200°C to 530°C to obtain the flow curves of log ε˙ versus log ε. The effect of grain size was also examined by varying the grain sizes through a proper thermomechanical treatment. The flow curves were found to be composite curves consisting of contributions from grain boundary sliding (GBS) and grain matrix deformation (GMD) at superplastic temperatures. The activation energy obtained for GMD was 124.9 kJ/mole in the temperature range from 470°C to 530°C, very similar to that for self-diffusion in pure Al

Modelling and Simulation of a River-Crossing Operation via Discrete Event Simulation with Engineering Details

From a military standpoint, a river is an area that should be avoided in a potential engagement because of lack of cover and the necessity of dividing the unit while crossing. Thus, a key point of a river-crossing operation is speed. Many efforts have been made to enable faster river crossing by improvement of tactics, techniques, and procedures (TTP). However, improvements in TTP are evaluated by modelling and simulation much less frequently than are the toe-to-toe engagements between two opposing forces, and to our knowledge, this is the first simulation model of brigade-level river crossing with engineering details. This study presents a simulation model of the river-crossing operation, applies real world parameters, and evaluates which tactics are preferable in a particular operational environments. This analysis has led to new operational methods of river crossing that have been suggested by experienced subject-matter experts. For instance, the current Republic of Korea Army Field Manual dictates to rotate river-crossing rafts in all situations, but our experiment suggests that no rotation is preferable when the width of river is less than 400 m based on the statistical analyses, which includes the regression-based meta-modelling and the ANOVA, of our simulation model that embodies the engineering details of river-crossing equipment.Defence Science Journal, Vol. 65, No. 2, March 2015, pp.135-143, DOI:http://dx.doi.org/10.14429/dsj.65.814

Machine Learning-Based Nicotine Addiction Prediction Models for Youth E-Cigarette and Waterpipe (Hookah) Users

Despite the harmful effect on health, e-cigarette and hookah smoking in youth in the U.S. has increased. Developing tailored e-cigarette and hookah cessation programs for youth is imperative. The aim of this study was to identify predictor variables such as social, mental, and environmental determinants that cause nicotine addiction in youth e-cigarette or hookah users and build nicotine addiction prediction models using machine learning algorithms. A total of 6511 participants were identified as ever having used e-cigarettes or hookah from the National Youth Tobacco Survey (2019) datasets. Prediction models were built by Random Forest with ReliefF and Least Absolute Shrinkage and Selection Operator (LASSO). ReliefF identified important predictor variables, and the Davies–Bouldin clustering evaluation index selected the optimal number of predictors for Random Forest. A total of 193 predictor variables were included in the final analysis. Performance of prediction models was measured by Root Mean Square Error (RMSE) and Confusion Matrix. The results suggested high performance of prediction. Identified predictor variables were aligned with previous research. The noble predictors found, such as ‘witnessed e-cigarette use in their household’ and ‘perception of their tobacco use’, could be used in public awareness or targeted e-cigarette and hookah youth education and for policymakers

Enhancing photoluminescence quantum efficiency of metal halide perovskites by examining luminescence-limiting factors

Metal halide perovskites (MHPs) show superior optoelectronic properties, which give them the great potential for use in next generation light-emitting diodes (LEDs). In particular, their narrow emission linewidths can achieve ultrahigh color purity. However, the reported luminescence efficiency (LE) values are not high enough to be commercialized in displays and solid-state lightings. Moreover, the operational stability of LEDs associated with the overshooting of luminance and the high relative standard deviation of reported external quantum efficiencies are still problematic. In this perspective, we review photophysical factors that limit the photoluminescence quantum efficiency of perovskite-based LEDs. These factors are categorized into (i) weak exciton binding, (ii) nonradiative recombinations, (iii) slow cooling of long-lived hot carriers, (iv) deep-level defects, and (v) interband transition rates. We then present various physicochemical methods to effectively overcome these luminescence-limiting factors. We finally suggest some useful research directions to further improve the LE of MHP emitters as core components in displays and solid-state lightings.

Characteristics of the Korean stock market correlations

In this study, we establish a network structure of the Korean stock market, one of the emerging markets, with its minimum spanning tree through the correlation matrix. Base on this analysis, it is found that the Korean stock market doesn't form the clusters of the business sectors or of the industry categories. When the MSCI (Morgan Stanley Capital International Inc.) index is exploited, we found that the clusters of the Korean stock market is formed. This finding implicates that the Korean market, in this context, is characteristically different form the mature markets.Comment: 11 pages, 3 figures, revised on June 200