Multifractal dimension spectrum analysis for nuclear density distribution.

We present an integral density method for calculating the multifractal dimension spectrum for nucleon distribution in atomic nuclei. This method is then applied to analyze the non-uniformity of density distribution in several typical types of nuclear matter distributions, including the Woods-Saxon distribution, halo structure, and tetrahedral α clustering. The subsequent discussion provides a comprehensive and detailed exploration of the results obtained. The multifractal dimension spectrum shows a remarkable sensitivity to the density distribution, establishing it as a simple and novel tool for studying the distribution of nucleons in nuclear multibody systems.

Exploring the Diversity of Nuclear Density through Information Entropy.

This study explores the role of information entropy in understanding nuclear density distributions, including both stable configurations and non-traditional structures such as neutron halos and α-clustering. By quantifying the uncertainty and disorder inherent in nucleon distributions in nuclear many-body systems, information entropy provides a macroscopic measure of the physical properties of the system. A more dispersed and disordered density distribution results in a higher value of information entropy. This intrinsic relationship between information entropy and system complexity allows us to quantify uncertainty and disorder in nuclear structures by analyzing various geometric parameters such as nuclear radius, diffuseness, neutron skin, and cluster structural features.

Unveiling the dynamics of little-bang nucleosynthesis.

High-energy nuclear collisions provide a unique site for the synthesis of both nuclei and antinuclei at temperatures of kT ≈ 100 - 150 MeV. In these little bangs of transient collisions, a quark-gluon plasma (QGP) of nearly vanishing viscosity is created, which is believed to have existed in the early universe within the first few microseconds after the Big Bang. Analyses of identified particles produced in these little bangs based on the statistical hadronization model for the QGP have suggested that light (anti)nuclei are produced from the QGP as other hadrons and their abundances are little affected by later hadronic dynamics. Here, we find a strong reduction of the triton yield by about a factor of 1.8 in high-energy heavy-ion collisions based on a kinetic approach that includes the effects of hadronic re-scatterings, particularly that due to pion-catalyzed multi-body reactions. This finding is supported by the latest experimental measurements and thus unveils the important role of hadronic dynamics in the little-bang nucleosynthesis.

The 5α condensate state in 20Ne.

The formed 4He (α) clusters consisting of two neutrons and two protons can be a building block in light nuclear systems. Intriguingly, these alpha clusters could potentially form alpha condensate states within the nuclear system. The Hoyle state at 7.65 MeV in 12C, which plays an essential role in stellar nucleosynthesis, is now considered to be a phase transition, namely the 3α Bose-Einstein condensate. Confirming the existence of Hoyle-analog states in Nα nuclei (N > 3) remains a major challenge. Here we show microscopic five-body calculations for the 20Ne nucleus. We find that one excited 0+ state has a distinct gas-like characteristic and represents the condensate state. Identifying the 5α condensate state is an important step in establishing the concept of α condensation in nuclear fermion systems.

Measurements of the lightest hypernucleus (HΛ3): progress and perspective.

The hyperon-nucleon (Y-N) interaction is important for the description of the equation-of-state of high baryon density matter. Hypernuclei, the cluster object of nucleons and hyperons, serve as cornerstones of a full understanding of the Y-N interaction. Recent measurements of the lightest known hypernucleus, the hypertriton's (HΛ3) and anti-hypertriton's (H¯Λ¯3) lifetime, mass and Λ separation energy have attracted interests on the subject. Its cross section and collective flow parameters have also been measured in heavy-ion collisions, which have revealed new features on its production mechanism. In this article we summarise recent measurements of HΛ3, focusing on the heavy-ion collisions. We will discuss their implications for the HΛ3 properties and the constrains on the Y-N interaction models.

Recursive traffic percolation on urban transportation systems.

This paper proposes a recursive traffic percolation framework to capture the dynamics of cascading failures and analyze potential overloaded bottlenecks. In particular, compared to current work, the influence of external flow is considered, providing a new perspective for the study of regional commuting. Finally, we present an empirical study to verify the accuracy and effectiveness of our framework. Further analysis indicates that external flows from different regions affect the network. Our work requires only primary data and verifies the improvement of the functional network.

Multilayer Network Analysis of Nuclear Reactions.

The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, (4)He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the ß-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart.

Myoclonic epilepsy with ragged-red fibers: A case report.

Myoclonic epilepsy with ragged-red fibers is a maternally inherited disease that is characterized by myoclonic epilepsy, cerebellar ataxia and progressive muscular weakness. The present study reports the case of a 25-year-old male who presented with paroxysmal left upper limb tics and weakness for two years. Neurological examination revealed intact cranial nerves, decreased deep tendon reflexes and decreased sensation of touch, pain and vibration. The gait of the patient was broad and he was unable to walk in a straight line. Local cortical atrophy was also observed in the left temporal-occipital cortex on a magnetic resonance imaging scan. The muscle biopsy revealed ragged-red fibers. Therefore, the present study hypothesized that imaging observations and follow-up examinations are important in patients with myoclonic epilepsy.

Origin of Gibrat law in Internet: asymmetric distribution of the correlation.

Although Gibrat's law and its generalized versions have been widely used, the organizing principle behind its phenomenological theory has been poorly studied for network-structured systems. More important, its fluctuation behavior, which contradicts the prediction of the preferential attachment (PA), indicates a nontrivial mechanism that goes beyond our present knowledge based on the traditional mean-field approach. Here, we take advantage of the rich data of the Internet and aim to identify the origin of Gibrat's law by studying the empirical fluctuation behavior. We show how the correlation between the fluctuations of the node degree increment affects the dynamics of the network. Specifically, if the distribution of the correlation is symmetric, the network evolves as the classical PA, while if such symmetry breaks, the fluctuation becomes macroscopically positively correlated and contributes to the emergence of Gibrat's law. These results indicate a local collective increase in the actual network evolution, which provides a new paradigm and understanding of the related microcosmic dynamics.

[The application of decision tree in the research of anemia among rural children under 3-year-old].

OBJECTIVE: To study the application of decision tree in the research of anemia among rural children. METHODS: In the Enterprise Miner module of software SAS 8.2, 3000 observations were sampled from database and the decision tree model was built. The model using decision tree of CART bases on Gini impurity index. RESULTS: The misclassification rate of decision tree model was, training set 21.2%, validation set 21.9%. The Root ASE of decision tree model was, training set 0.399, validation set 0.404. The area under the ROC curve was larger than the reference line. The diagnostic chart showed that the corresponding percentage was higher than the other. The decision tree model selected 9 important factors and ranked them by their power, among which mother of anemia (1.00) was the most important factor. Others were children's age (0.75), time of ablactation (0.53), mother's age (0.32), the time of egg supplementation (0.26), category of the project county (0.26), the time of milk supplementation (0.16), number of people in the family (0.13), the education status of the mother (0.12). Decision tree produced simple and easy rules that might be used to classify and predict in the same research. CONCLUSION: Decision tree could screen out the important factors of anemia and identify the cutting-points for factors. With the wide application of decision tree, it would exhibit important application values in the research of the rural children health care.