Gravity model explained by the radiation model on a population landscape

Understanding the mechanisms behind human mobility patterns is crucial to improve our ability to optimize and predict traffic flows. Two representative mobility models, i.e., radiation and gravity models, have been extensively compared to each other against various empirical data sets, while their fundamental relation is far from being fully understood. In order to study such a relation, we first model the heterogeneous population landscape by generating a fractal geometry of sites and then by assigning to each site a population independently drawn from a power-law distribution. Then the radiation model on this population landscape, which we call the radiation-on-landscape (RoL) model, is compared to the gravity model to derive the distance exponent in the gravity model in terms of the properties of the population landscape, which is confirmed by the numerical simulations. Consequently, we provide a possible explanation for the origin of the distance exponent in terms of the properties of the heterogeneous population landscape, enabling us to better understand mobility patterns constrained by the travel distance.Comment: 14 pages, 4 figure

A common trajectory recapitulated by urban economies

Is there a general economic pathway recapitulated by individual cities over and over? Identifying such evolution structure, if any, would inform models for the assessment, maintenance, and forecasting of urban sustainability and economic success as a quantitative baseline. This premise seems to contradict the existing body of empirical evidences for path-dependent growth shaping the unique history of individual cities. And yet, recent empirical evidences and theoretical models have amounted to the universal patterns, mostly size-dependent, thereby expressing many of urban quantities as a set of simple scaling laws. Here, we provide a mathematical framework to integrate repeated cross-sectional data, each of which freezes in time dimension, into a frame of reference for longitudinal evolution of individual cities in time. Using data of over 100 millions employment in thousand business categories between 1998 and 2013, we decompose each city's evolution into a pre-factor and relative changes to eliminate national and global effects. In this way, we show the longitudinal dynamics of individual cities recapitulate the observed cross-sectional regularity. Larger cities are not only scaled-up versions of their smaller peers but also of their past. In addition, our model shows that both specialization and diversification are attributed to the distribution of industry's scaling exponents, resulting a critical population of 1.2 million at which a city makes an industrial transition into innovative economies

A house price valuation based on the random forest approach: the mass appraisal of residential property in South Korea

Mass appraisal is the standardized procedure of valuing a large number of properties at the same time and is commonly used to compute real estate tax. While a hedonic pricing model based on the ordinary least squares (OLS) linear regression has been employed as the traditional method in this process, the stability and accuracy of the model remain questionable. This paper investigates the features of a house price predictor based on the Random Forest (RF) method by comparing it with that of a conventional hedonic pricing model. We used apartment transaction data from the period of 2006 to 2017 in the district of Gangnam, one of the most developed areas in South Korea. Using a data set covering 40% of all transactions in the sample area, we demonstrate that the accuracy of a machine learning-based predictor can be surprisingly high. The average of percentage deviations between the predicted and the actual market price was found to be only around 5.5% in the RF predictor, whereas it was almost 20% in the OLS-based predictor. With the RF predictor, the probability of the predicted price being within 5% of its actual market price was 72%, while only about 17.5% of the regression-based predictions fell within the same range. These results show that, in the practice of mass appraisal, the RF method may be a useful complement to the hedonic models, as it more adequately captures the complexity or non-linearity of actual housing markets. First published online 03 February 202

Measuring national capability over big science's multidisciplinarity: A case study of nuclear fusion research

In the era of big science, countries allocate big research and development budgets to large scientific facilities that boost collaboration and research capability. A nuclear fusion device called the "tokamak" is a source of great interest for many countries because it ideally generates sustainable energy expected to solve the energy crisis in the future. Here, to explore the scientific effects of tokamaks, we map a country's research capability in nuclear fusion research with normalized revealed comparative advantage on five topical clusters-material, plasma, device, diagnostics, and simulation-detected through a dynamic topic model. Our approach captures not only the growth of China, India, and the Republic of Korea but also the decline of Canada, Japan, Sweden, and the Netherlands. Time points of their rise and fall are related to tokamak operation, highlighting the importance of large facilities in big science. The gravity model points out that two countries collaborate less in device, diagnostics, and plasma research if they have comparative advantages in different topics. This relation is a unique feature of nuclear fusion compared to other science fields. Our results can be used and extended when building national policies for big science.11Yscopu

Importance of remission and residual somatic symptoms in health-related quality of life among outpatients with major depressive disorder: a cross-sectional study

Background: Major depressive disorder (MDD) is strongly associated with an impaired quality of life (QoL), which is itself affected by various factors. Symptom-oriented ratings poorly reflect the impact of disease on the QoL and level of functioning of the mental health of subjects. The purpose of this study was to assess health-related QoL (HRQoL) using preference-based measures in outpatients with MDD with regard to their remission achievement and clinical factors affecting the HRQoL. Methods: This was a cross-sectional observational study. We recruited 811 patients with MDD from 14 psychiatric outpatient clinics in Korea. They were divided into three groups as follows: a new visit group (n = 287), a remitted group (n = 235), and a non-remitted group (n = 289). The 17-item Hamilton Depression Rating Scale was used to assign patients to the remitted or non-remitted group. The general HRQoL was assessed with the EuroQol 5D (EQ-5D), using both the EQ-5D index score and the EuroQol Visual Analog Scale (EQ-VAS). The disease-specific HRQoL was assessed with the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (Q-LES-Q-SF). Results: The non-remitted group showed a significant impairment of HRQoL in view of the subscales of EQ-5D index scores, EQ-VAS, and Q-LES-Q-SF. The EQ-5D index score in the remitted group was 0.77 ± 0.10, while it was 0.57 ± 0.23 in the non-remitted group and 0.58 ± 0.24 in the new visit group (p < 0.0001). The EQ-VAS scores for the remitted and non-remitted groups were 72.5 ± 16.6 and 50.9 ± 20.3, respectively (p < 0.0001). Likewise, patients with remission had the Q-LES-Q-SF total score of 46.5 ± 8.8, whereas those with non-remission reported 36.7 ± 7.7 (p < 0.0001). The symptom severity measured by the Depression and Somatic Symptoms Scale was significantly correlated with the HRQoL. Furthermore, patients with severe somatic symptoms showed a significantly lower EQ-5D index score (0.54 ± 0.24) than those with mild/moderate somatic symptoms (0.75 ± 0.12; p = 0.002). Conclusion: Non-remitted MDD patients, especially those with more severe somatic symptoms, show a distinct impairment of HRQoL and more clinical symptoms, suggesting the importance of achieving remission in the treatment of MDD

Oscillation Control Algorithms for Resonant Sensors with Applications to Vibratory Gyroscopes

We present two oscillation control algorithms for resonant sensors such as vibratory gyroscopes. One control algorithm tracks the resonant frequency of the resonator and the other algorithm tunes it to the specified resonant frequency by altering the resonator dynamics. Both algorithms maintain the specified amplitude of oscillations. The stability of each of the control systems is analyzed using the averaging method, and quantitative guidelines are given for selecting the control gains needed to achieve stability. The effects of displacement measurement noise on the accuracy of tracking and estimation of the resonant frequency are also analyzed. The proposed control algorithms are applied to two important problems in a vibratory gyroscope. The first is the leading-following resonator problem in the drive axis of MEMS dual-mass vibratory gyroscope where there is no mechanical linkage between the two proof-masses and the second is the on-line modal frequency matching problem in a general vibratory gyroscope. Simulation results demonstrate that the proposed control algorithms are effective. They ensure the proof-masses to oscillate in an anti-phase manner with the same resonant frequency and oscillation amplitude in a dual-mass gyroscope, and two modal frequencies to match in a general vibratory gyroscope