Spatial thinking in geographic information science: a review of past studies and prospects for the future

AbstractIn recent years, the relationship between geographic information science (GIScience) and spatial thinking has attracted much attention in English-speaking countries. Nevertheless, vagueness remains concerning the concept of spatial thinking and its components. The aim of this paper is to review previous studies on the relationship between GIScience and spatial thinking, and to clarify the elements of spatial thinking and related terms. After discussing the basic elements of spatial thinking, it explores the relationship between GIScience and spatial thinking by dividing it into two aspects: the role of geographic information systems (GIS) in education on spatial thinking, and the role of spatial thinking in GIScience. Concerning the former, potential roles of GIS in spatial thinking education, particularly in geography and STEM disciplines, are suggested. Concerning the latter, the relationships between the body of knowledge on GIS education and the elements of spatial thinking are examined. Finally, the present situation and future prospects for studies on spatial thinking and GIScience in Japan are briefly discussed

A neural network system for transformation of regional cuisine style

We propose a novel system which can transform a recipe into any selected regional style (e.g., Japanese, Mediterranean, or Italian). This system has two characteristics. First the system can identify the degree of regional cuisine style mixture of any selected recipe and visualize such regional cuisine style mixtures using barycentric Newton diagrams. Second, the system can suggest ingredient substitutions through an extended word2vec model, such that a recipe becomes more authentic for any selected regional cuisine style. Drawing on a large number of recipes from Yummly, an example shows how the proposed system can transform a traditional Japanese recipe, Sukiyaki, into French style

Socioeconomic Status and Health Communication Inequalities in Japan: A Nationwide Cross-Sectional Survey

Background: Considerable evidence suggests that communication inequality is one potential mechanism linking social determinants, particularly socioeconomic status, and health inequalities. This study aimed to examine how dimensions of health communication outcomes (health information seeking, self-efficacy, exposure, and trust) are patterned by socioeconomic status in Japan. Methods: Data of a nationally representative cross-sectional survey of 2,455 people aged 15–75 years in Japan were used for secondary analysis. Measures included socio-demographic characteristics, subjective health, recent health information seeking, self-efficacy in seeking health information, and exposure to and trust in health information from different media. Results: A total of 1,311 participants completed the questionnaire, giving a response rate of 53.6%. Multivariate logistic regression revealed that education and household income, but not employment, were significantly associated with health information seeking and self-efficacy. Socioeconomic status was not associated with exposure to and trust in health information from mass media, but was significantly associated with health information from healthcare providers and the Internet. Conclusion: Health communication outcomes were patterned by socioeconomic status in Japan thus demonstrating the prevalence of health communication inequalities. Providing customized exposure to and enhancing the quality of health information by considering social determinants may contribute to addressing social disparities in health in Japan

A computational neuroscience perspective on subjective wellbeing within the active inference framework

Understanding and promoting subjective wellbeing (SWB) has been the topic of increasing research, due in part to its potential contributions to health and productivity. To date, the conceptualization of SWB has been grounded within social psychology and largely focused on self-report measures. In this paper, we explore the potentially complementary tools and theoretical perspectives offered by computational neuroscience, with a focus on the active inference (AI) framework. This framework is motivated by the fact that the brain does not have direct access to the world; to select actions, it must instead infer the most likely external causes of the sensory input it receives from both the body and the external world. Because sensory input is always consistent with multiple interpretations, the brain’s internal model must use background knowledge, in the form of prior expectations, to make a “best guess” about the situation it is in and how it will change by taking one action or another. This best guess arises by minimizing an error signal representing the deviation between predicted and observed sensations given a chosen action—quantified mathematically by a variable called free energy (FE). Crucially, recent proposals have illustrated how emotional experience may emerge within AI as a natural consequence of the brain keeping track of the success of its model in selecting actions to minimize FE. In this paper, we draw on the concepts and mathematics in AI to highlight how different computational strategies can be used to minimize FE—some more successfully than others. This affords a characterization of how diverse individuals may adopt unique strategies for achieving high SWB. It also highlights novel ways in which SWB could be effectively improved. These considerations lead us to propose a novel computational framework for understanding SWB. We highlight several parameters in these models that could explain individual and cultural differences in SWB, and how they might inspire novel interventions. We conclude by proposing a line of future empirical research based on computational modelling that could complement current approaches to the study of wellbeing and its improvement

Active Exploration based on Information Gain by Particle Filter for Efficient Spatial Concept Formation

Autonomous robots are required to actively and adaptively learn the categories and words of various places by exploring the surrounding environment and interacting with users. In semantic mapping and spatial language acquisition conducted using robots, it is costly and labor-intensive to prepare training datasets that contain linguistic instructions from users. Therefore, we aimed to enable mobile robots to learn spatial concepts through autonomous active exploration. This study is characterized by interpreting the `action' of the robot that asks the user the question `What kind of place is this?' in the context of active inference. We propose an active inference method, spatial concept formation with information gain-based active exploration (SpCoAE), that combines sequential Bayesian inference by particle filters and position determination based on information gain in a probabilistic generative model. Our experiment shows that the proposed method can efficiently determine a position to form appropriate spatial concepts in home environments. In particular, it is important to conduct efficient exploration that leads to appropriate concept formation and quickly covers the environment without adopting a haphazard exploration strategy

Bragg x-ray ptychography of a silicon crystal: Visualization of the dislocation strain field and the production of a vortex beam

We experimentally demonstrate the visualization of nanoscale dislocation strain fields in a thick silicon single crystal by a coherent diffraction imaging technique called Bragg x-ray ptychography. We also propose that the x-ray microbeam carrying orbital angular momentum is selectively produced by coherent Bragg diffraction from dislocation singularities in crystals. This work not only provides us with a tool for characterizing dislocation strain fields buried within extended crystals but also opens up new scientific opportunities in femtosecond spectroscopy using x-ray free-electron lasers.Yukio Takahashi, Akihiro Suzuki, Shin Furutaku, Kazuto Yamauchi, Yoshiki Kohmura, and Tetsuya Ishikawa, Phys. Rev. B 87, 121201, 2013

High-resolution and high-sensitivity phase-contrast imaging by focused hard x-ray ptychography with a spatial filter

We demonstrate high-resolution and high-sensitivity x-ray phase-contrast imaging of a weakly scattering extended object by scanning coherent diffractive imaging, i.e., ptychography, using a focused x-ray beam with a spatial filter. We develop the x-ray illumination optics installed with the spatial filter to collect coherent diffraction patterns with a high signal-to-noise ratio. We quantitatively visualize the object with a slight phase shift ([formula omitted]) at spatial resolution better than 17 nm in a field of view larger than [formula omitted]. The present coherent method has a marked potential for high-resolution and wide-field-of-view observation of weakly scattering objects such as biological soft tissues.Yukio Takahashi, Akihiro Suzuki, Shin Furutaku, Kazuto Yamauchi, Yoshiki Kohmura, and Tetsuya Ishikawa, "High-resolution and high-sensitivity phase-contrast imaging by focused hard x-ray ptychography with a spatial filter", Appl. Phys. Lett. 102, 094102 (2013) https://doi.org/10.1063/1.4794063

Multiscale element mapping of buried structures by ptychographic x-ray diffraction microscopy using anomalous scattering

We propose an element mapping technique of nano-meso-microscale structures buried within large and/or thick objects by ptychographic x-ray diffraction microscopy using anomalous scattering. We performed quantitative imagings of both the electron density and Au element of Au/Ag nanoparticles at the pixel resolution of better than 10 nm in a field of view larger than 5 × 5 μm2 by directly phasing ptychographic coherent diffraction patterns acquired at two x-ray energies below the Au L3 edge. This method provides us with multiscale structural and elemental information for understanding the element/property relationship linking nanoscale structures to macroscopic functional properties in material and biological systems. © 2011 American Institute of Physics.Yukio Takahashi, Akihiro Suzuki, Nobuyuki Zettsu, Yoshiki Kohmura, Kazuto Yamauchi, and Tetsuya Ishikawa, "Multiscale element mapping of buried structures by ptychographic x-ray diffraction microscopy using anomalous scattering", Appl. Phys. Lett. 99(13), 131905 (2011) https://doi.org/10.1063/1.3644396

Implantation of Autologous Bone-Marrow-Derived Cells Reconstructs Functional Urethral Sphincters in Rabbits

The purpose of this study was to determine if implantation of autologous bone-marrow-derived cells has the potential to treat stress urinary incontinence caused by intrinsic sphincter deficiency. Bone marrow cells harvested from femurs of New Zealand White rabbits were cultured for 10 days. Seven days before implantation, the urethral sphincters located at the internal urethral orifice were cryo-injured by spraying liquid nitrogen for 15 s. The cultured autologous bone-marrow-derived cells were implanted 7 days after cryo-injury. For controls, cell-free solutions were injected. At 7 and 14 days after implantation, leak point pressures were determined and the urethral sphincters were examined by immunohistochemistry. At 7 and 14 days, the cell-implanted regions contained numerous striated and smooth muscle-like cells expressing myoglobin and smooth muscle actin, respectively. The proportions of myoglobin- and smooth muscle actin-expressing areas in both the 7- and 14-day cell-implanted regions were significantly higher than in controls. By 14 days, these differentiated cells formed contacts with similar cells, creating layered muscle structures. At that time, the leak point pressure of the cell-implanted rabbits was significantly higher than that of the controls. In conclusion, autologous bone-marrow-derived cells can reconstruct functional urethral sphincters.ArticleTISSUE ENGINEERING PART A. 17(41098):1069-1081 (2011)journal articl