Testing the Power-Law Hypothesis of the Inter-Conflict Interval

The severity of war, measured by battle deaths, follows a power-law distribution. Here, we demonstrate that power law also holds in the temporal aspects of interstate conflicts. A critical quantity is the inter-conflict interval (ICI), the interval between the end of a conflict in a dyad and the start of the subsequent conflict in the same dyad. Using elaborate statistical tests, we confirmed that the ICI samples compiled from the history of interstate conflicts from 1816 to 2014 followed a power-law distribution. We propose an information-theoretic model to account for the power-law properties of ICIs. The model predicts that a series of ICIs in each dyad is independently generated from an identical power-law distribution. This was confirmed by statistical examination of the autocorrelation of the ICI series. Our findings help us understand the nature of wars between normal states, the significance of which has increased since the Russian invasion of Ukraine in 2022

Inverse square Levy walk emerging universally in goal-oriented tasks

The Levy walk in which the frequency of occurrence of step lengths follows a power-law distribution, can be observed in the migratory behavior of organisms at various levels. Levy walks with power exponents close to 2 are observed, and the reasons are unclear. This study aims to propose a model that universally generates inverse square Levy walks (called Cauchy walks) and to identify the conditions under which Cauchy walks appear. We demonstrate that Cauchy walks emerge universally in goal-oriented tasks. We use the term "goal-oriented" when the goal is clear, but this can be achieved in different ways, which cannot be uniquely determined. We performed a simulation in which an agent observed the data generated from a probability distribution in a two-dimensional space and successively estimated the central coordinates of that probability distribution. The agent has a model of probability distribution as a hypothesis for data-generating distribution and can modify the model such that each time a data point is observed, thereby increasing the estimated probability of occurrence of the observed data. To achieve this, the center coordinates of the model must be moved closer to those of the observed data. However, in the case of a two-dimensional space, arbitrariness arises in the direction of correction of the center; this task is goal oriented. We analyze two cases: a strategy that allocates the amount of modification randomly in the x- and y-directions, and a strategy that determines allocation such that movement is minimized. The results reveal that when a random strategy is used, the Cauchy walk appears. When the minimum strategy is used, the Brownian walk appears. The presence or absence of the constraint of minimizing the amount of movement may be a factor that causes the difference between Brownian and Levy walks

CLASSIFICATION OF BIPOLAR DISORDER, MAJOR DEPRESSIVE DISORDER, AND HEALTHY STATE USING VOICE

Objective: In this study, we propose a voice index to identify healthy individuals, patients with bipolar disorder, and patients with major depressive disorder using polytomous logistic regression analysis.Methods: Voice features were extracted from voices of healthy individuals and patients with mental disease. Polytomous logistic regression analysis was performed for some voice features.Results: With the prediction model obtained using the analysis, we identified subject groups and were able to classify subjects into three groups with 90.79% accuracy.Conclusion: These results show that the proposed index may be used as a new evaluation index to identify depression

Electronic Spatial Structures of Eigenstates in Amorphous Alloys

この論文は国立情報学研究所の電子図書館事業により電子化されました。A simple method is proposed for calculating the spatial extensions of wave functions in a tightbinding system. By means of the cluster Green functions, site-coefficients (amplitudes of the Wannier functions) of central sites in various type clusters within the system are derived, and the structures of the wavefunctions are discussed. As an example, the theoretical results for a ternary alloy are obtained and compared with the results from exact calculation of the 300-site model

Association between birth weight and massive haemorrhage in pregnancy with a low-lying placenta: a 9-year single-centre retrospective cohort study in Japan

A low-lying placenta is a well-known cause of a massive intrapartum haemorrhage. We aimed to evaluate whether neonatal birth weight deviation from the nationwide average could predict a massive haemorrhage during a delivery in the women with a low-lying placenta. This study included 40 women. The main outcomes were a massive haemorrhage and a neonatal birth weight deviation. We used a receiver operating characteristic curve analysis to determine the optimal birth weight deviation cut-off for predicting a massive haemorrhage. A multiple logistic regression model was used to identify the variables significantly associated with a massive haemorrhage. The best cut-off for predicting a massive haemorrhage was a birth weight deviation of +0.51 standard deviations (SDs) from the nationwide average. A birth weight deviation of ≥ +0.51 SDs was significantly associated with an increased massive haemorrhage risk.Impact statement What is already known on this subject? A low-lying placenta is a well-known cause of a massive intrapartum haemorrhage. Therefore, when managing pregnancies with a low-lying placenta, the possibility of severe perinatal bleeding should be considered, and it is desirable to determine reliable predictors of a haemorrhage. However, few studies have reported the predictive factors of a massive haemorrhage in patients with a low-lying placenta. What do the results of this study add? We demonstrated that a birth weight deviation from the nationwide average was significantly associated with a massive intrapartum haemorrhage in patients with a low-lying placenta. To our knowledge, this is the first study to clarify the association between a neonatal birth weight and a massive intrapartum haemorrhage incidence and to determine the optimal birth weight deviation cut-off for predicting a massive haemorrhage in patients with a low-lying placenta. What are the implications of these findings for clinical practice and/or further research? An accurate risk stratification using the foetal weight as a marker for a predicting massive intrapartum haemorrhage may help in the management of patients with a low-lying placenta. Studies with a larger sample size are required to confirm our findings

Risk assessment of shoulder dystocia via the difference between transverse abdominal and biparietal diameters: A retrospective observational cohort study.

Shoulder dystocia is defined as vaginal cephalic delivery that requires additional obstetric maneuvers to deliver the fetus after the head has been delivered and gentle traction has failed. A bigger difference between the transverse abdominal diameter (TAD) (abdominal circumference [AC]/π) and biparietal diameter (BPD) (TAD-BPD) has been reported as a risk factor for shoulder dystocia in different countries; however, it remains unclear if this relationship is relevant in Japan. This study aimed to clarify the association between TAD-BPD and shoulder dystocia after adjusting for potential confounding factors in a Japanese cohort. We retrospectively examined 1,866 Japanese women who delivered vaginally between 37+0 and 41+6 weeks of gestation at the University of Yamanashi Hospital between June 2012 and November 2018. The cutoff value of TAD-BPD associated with shoulder dystocia and the association between TAD-BPD and shoulder dystocia were evaluated. The mean maternal age was 32.5±5.3 years; the patients included 1,053 nulliparous women (57.5%), 915 male infants (49.0%), 154 women with gestational diabetes mellitus (GDM) (8.3%), and 5 infants with macrosomia (0.3%). The mean TAD-BPD was 9.03±4.7 mm. The overall incidence of shoulder dystocia was 2.4% (44/1866). The cutoff value to predict shoulder dystocia was 12.0 mm (sensitivity, 61.4%; specificity, 73.8%; likelihood ratio, 2.34; positive predictive value, 5.4%; negative predictive value, 98.8%). We then used a multivariable logistic regression analysis to examine the association between TAD-BPD and shoulder dystocia while controlling for the potential confounding factors. In multivariate analyses, TAD-BPD ≥12.0 mm (adjusted odds ratio [OR], 4.39; 95% confidence interval [CI], 2.35-8.18) and GDM (adjusted OR, 3.59; 95% CI, 1.71-7.52) were associated with shoulder dystocia. Although TAD-BPD appears to be a relevant risk factor for shoulder dystocia, sonographic fetal anthropometric measures do not appear to be useful in screening for shoulder dystocia due to a low positive predictive value