Effects of the distant population density on spatial patterns of demographic dynamics

Spatiotemporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focussing on internal (i.e., domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e., cells of size 500 m $\times$ 500 m) for the entirety of the country and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a radius of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a radius of $\approx 1$ km.Comment: 22 figures, 2 tables, fixed an incorrect publication yea

Win-stay lose-shift strategy in formation changes in football

Managerial decision making is likely to be a dominant determinant of performance of teams in team sports. Here we use Japanese and German football data to investigate correlates between temporal patterns of formation changes across matches and match results. We found that individual teams and managers both showed win-stay lose-shift behavior, a type of reinforcement learning. In other words, they tended to stick to the current formation after a win and switch to a different formation after a loss. In addition, formation changes did not statistically improve the results of succeeding matches.The results indicate that a swift implementation of a new formation in the win-stay lose-shift manner may not be a successful managerial rule of thumb.Comment: 7 figures, 11 table

Population changes in residential clusters in Japan

Population dynamics in urban and rural areas are different. Understanding factors that contribute to local population changes has various socioeconomic and political implications. In the present study, we use population census data in Japan to examine contributors to the population growth of residential clusters between years 2005 and 2010. The data set covers the entirety of Japan and has a high spatial resolution of 500$\times$500$\textrm{m}^2$, enabling us to examine population dynamics in various parts of the country (urban and rural) using statistical analysis. We found that, in addition to the area, population density, and age, the shape of the cluster and the spatial distribution of inhabitants within the cluster are significantly related to the population growth rate of a residential cluster. Specifically, the population tends to grow if the cluster is "round" shaped (given the area) and the population is concentrate near the center rather than periphery of the cluster.Comment: 3 figures, 4 table

Predictors of cognitive function in patients with hypothalamic hamartoma following stereotactic radiofrequency thermocoagulation surgery

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138275/1/epi13838.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138275/2/epi13838_am.pd

Estimating Body Stiffness in Quadrupedal Locomotion using the Flexible Shoulder as a Physical Reservoir

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P1

Twisted mass transport enabled by the angular momentum of light

The authors acknowledge support in the form of KAKENHI Grants-in-Aid (Grant Nos. JP 16H06507, JP 17K19070, and JP 18H03884) from the Japan Society for the Promotion of Science (JSPS), Japan Science and Technology Agency (JST) CREST Grant No. (JPMJCR1903), and the U.S. National Science Foundation Award #1809518. KD and YA thank the UK Engineering and Physical Sciences Research Council for funding (through Grant No. EP/P030017/1).Light may carry both orbital angular momentum (AM) and spin AM. The former is a consequence of its helical wavefront, and the latter is a result of its rotating transverse electric field. Intriguingly, the light–matter interaction with such fields shows that the orbital AM of light causes a physical “twist” in a range of materials, including metal, silicon, azopolymer, and even liquid-phase resin. This process may be aided by the light’s spin AM, resulting in the formation of various helical structures. The exchange between the AM of light and matter offers not only unique helical structures at the nanoscale but also entirely novel fundamental phenomena with regard to the light–matter interaction. This will lead to the future development of advanced photonics devices, including metamaterials for highly sensitive detectors as well as reactions for chiral chemical composites. Here, we focus on interactions between the AM of light and azopolymers, which exhibit some of the most diverse structures and phenomena observed. These studies result in helical surface relief structures in azopolymers and will leverage next-generation applications with light fields carrying optical AM.Publisher PDFPeer reviewe

Impact of the Coronary Flow Reduction at Rest on Myocardial Perfusion and Functional Indices Derived from Myocardial Contrast and Strain Echocardiography

Background: The severity of the coronary flow reduction that corresponds to myocardial perfusion and functional abnormalities remains unclear. We estimated the impact of various severities of flow-limiting coronary stenosis at rest on myocardial perfusion and functional indices from myocardial contrast echocardiography and tissue strain imaging and characterized the relationship between both the indices. Methods: Four levels of flow-limiting stenoses (slight, mild, moderate, severe) of the left circumflex coronary artery were examined in 10 open-chest dogs. In the left circumflex coronary artery area, plateau videointensity and time to plateau (TP) of the replenishment curve from myocardial contrast echocardiography were calculated for perfusion analysis, and peak systolic strain and postsystolic strain index (PSI) from tissue strain imaging were measured for functional analysis. Results: Plateau videointensity and peak systolic strain tended to decrease with increased severity of stenosis, although these differences did not reach the level of statistical significance. TP and PSI were significantly increased in the context of moderate (≥30-<50%) and severe (≥50%) flow reduction when compared to baseline values (TP, moderate 1.69 ± 0.20 and severe 1.77 ± 0.25 vs baseline 0.93 ± 0.17, P < .01, respectively; PSI, moderate 0.96 ± 0.15 and severe 1.28 ± 0.32 vs baseline 0.59 ± 0.18, P < .05 and P < .01, respectively). Further, TP and PSI were positively correlated with flow reduction (r = 0.81 and r = 0.84, P < .0001, respectively), and PSI was positively correlated with TP (r = 0.72, P < .0001). Conclusions: In contrast to conventional indices, such as plateau videointensity and peak systolic strain, novel indices, such as TP and PSI, were both able to detect 30% or greater coronary flow reduction at rest. © 2006 American Society of Echocardiography.Okuda K, Asanuma T, Hirano T, Masuda K, Otani K, Ishikura F, Beppu S. Impact of the coronary flow reduction at rest on myocardial perfusion and functional indices derived from myocardial contrast and strain echocardiography. J Am Soc Echocardiogr. 2006 Jun;19(6):781-7. doi: 10.1016/j.echo.2005.10.016

Deep Learning Predicts Rapid Over-softening and Shelf Life in Persimmon Fruits

In contrast to the progress in the research on physiological disorders relating to shelf life in fruit crops, it has been difficult to non-destructively predict their occurrence. Recent high-tech instruments have gradually enabled non-destructive predictions for various disorders in some crops, while there are still issues in terms of efficiency and costs. Here, we propose application of a deep neural network (or simply deep learning) to simple RGB images to predict a severe fruit disorder in persimmon, rapid over-softening. With 1,080 RGB images of ‘Soshu’ persimmon fruits, three convolutional neural networks (CNN) were examined to predict rapid over-softened fruits with a binary classification and the date to fruit softening. All of the examined CNN models worked successfully for binary classification of the rapid over-softened fruits and the controls with > 80% accuracy using multiple criteria. Furthermore, the prediction values (or confidence) in the binary classification were correlated to the date to fruit softening. Although the features for classification by deep learning have been thought to be in a black box by conventional standards, recent feature visualization methods (or “explainable” deep learning) has allowed identification of the relevant regions in the original images. We applied Grad-CAM, Guided backpropagation, and layer-wise relevance propagation (LRP), to find early symptoms for CNNs classification of rapid over-softened fruits. The focus on the relevant regions tended to be on color unevenness on the surface of the fruit, especially in the peripheral regions. These results suggest that deep learning frameworks could potentially provide new insights into early physiological symptoms of which researchers are unaware