An elitism-based multi-objective evolutionary algorithm for min-cost network disintegration

Network disintegration or strengthening is a significant problem, which is widely used in infrastructure construction, social networks, infectious disease prevention and so on. But most studies assume that the cost of attacking anyone node is equal. In this paper, we investigate the robustness of complex networks under a more realistic assumption that costs are functions of degrees of nodes. A multi-objective, elitism-based, evolutionary algorithm (MOEEA) is proposed for the network disintegration problem with heterogeneous costs. By defining a new unit cost influence measure of the target attack node and combining with an elitism strategy, some combination nodes’ information can be retained. Through an ingenious update mechanism, this information is passed on to the next generation to guide the population to move to more promising regions, which can improve the rate of convergence of the proposed algorithm. A series of experiments have been carried out on four benchmark networks and some model networks, the results show that our method performs better than five other state-of-the-art attack strategies. MOEEA can usually find min-cost network disintegration solutions. Simultaneously, through testing different cost functions, we find that the stronger the cost heterogeneity, the better performance of our algorithm

As diversity increases, people paradoxically perceive social groups as more similar

With globalization and immigration, societal contexts differ in sheer variety of resident social groups. Social diversity challenges individuals to think in new ways about new kinds of people and where their groups all stand, relative to each other. However, psychological science does not yet specify how human minds represent social diversity, in homogeneous or heterogenous contexts. Mental maps of the array of society’s groups should differ when individuals inhabit more and less diverse ecologies. Nonetheless, predictions disagree on how they should differ. Confirmation bias suggests more diversity means more stereotype dispersion: With increased exposure, perceivers’ mental maps might differentiate more among groups, so their stereotypes would spread out (disperse). In contrast, individuation suggests more diversity means less stereotype dispersion, as perceivers experience within-group variety and between-group overlap. Worldwide, nationwide, individual, and longitudinal datasets (n = 12,011) revealed a diversity paradox: More diversity consistently meant less stereotype dispersion. Both contextual and perceived ethnic diversity correlate with decreased stereotype dispersion. Countries and US states with higher levels of ethnic diversity (e.g., South Africa and Hawaii, versus South Korea and Vermont), online individuals who perceive more ethnic diversity, and students who moved to more ethnically diverse colleges mentally represent ethnic groups as more similar to each other, on warmth and competence stereotypes. Homogeneity shows more-differentiated stereotypes; ironically, those with the least exposure have the most-distinct stereotypes. Diversity means less-differentiated stereotypes, as in the melting pot metaphor. Diversity and reduced dispersion also correlate positively with subjective wellbeing.info:eu-repo/semantics/publishedVersio

Retinal image enhancement via a multiscale morphological approach with OCCO filter.

Retinal images are widely used for diagnosis and eye disease detection. However, due to the acquisition process, retinal images often have problems such as low contrast, blurry details or artifacts. These problems may severely affect the diagnosis. Therefore, it is very impor tant to enhance the visual quality of such images. Contrast enhancement is a pre-processing applied to images to improve their visual quality. This technique betters the identification of retinal structures in degraded reti nal images. In this work, a novel algorithm based on multi-scale mathe matical morphology is presented. First, the original image is blurred us ing the Open-Close Close-Open (OCCO) filter to reduce any artifacts in the image. Next, multiple bright and dark features are extracted from the filtered image by the Top-Hat transform. Finally, the maximum bright values are added to the original image and the maximum dark values are subtracted from the original image, previously adjusted by a weight. The algorithm was tested on 397 retinal images from the public STARE database. The proposed algorithm was compared with state of the art al gorithms and results show that the proposal is more efficient in improving contrast, maintaining similarity with the original image and introducing less distortion than the other algorithms. According to ophthalmologists, the algorithm, by improving retinal images, provides greater clarity in the blood vessels of the retina and would facilitate the identification of pathologies.CONACYT - Consejo Nacional de Ciencia y TecnologíaPROCIENCI

Light cone structure near null infinity of the Kerr metric

Motivated by our attempt to understand the question of angular momentum of a relativistic rotating source carried away by gravitational waves, in the asymptotic regime near future null infinity of the Kerr metric, a family of null hypersurfaces intersecting null infinity in shearfree (good) cuts are constructed by means of asymptotic expansion of the eikonal equation. The geometry of the null hypersurfaces as well asthe asymptotic structure of the Kerr metric near null infinity are studied. To the lowest order in angular momentum, the Bondi-Sachs form of the Kerr metric is worked out. The Newman-Unti formalism is then further developed, with which the Newman-Penrose constants of the Kerr metric are computed and shown to be zero. Possible physical implications of the vanishing of the Newman-Penrose constants of the Kerr metric are also briefly discussed

Evaluation of genetic diversity in the golden apple snail, Pomacea canaliculata (Lamarck), from different geographical populations in China by inter simple sequence repeat (ISSR)

The genetic diversity of Pomacea canaliculata, collected from Los Banos (LB) in Philippines and Yuyao (YY), Taizhou (TZ), Fuzhou (FZ), Guangzhou (GZ), Nanning (NN), Kunming (KM) in China, was studied by using the inter simple sequence repeat (ISSR) technique. A total of 498 loci from 140 individuals were amplified with four selected ISSR primers and the percentage of polymorphic loci was 87.35%. At the species level, the Nei's gene diversity (H) was 0.3805 and the Shannon information diversity index (I) was 0.5607. A relatively high level of genetic differentiation among populations was detected based on Nei’s gene diversity analysis (Gst = 0.2001) and analysis of molecular variance (AMOVA) analysis (Φst = 0.0824), indicating the vast majority of genetic variation that occur within the populations. The limited genetic distance (0.0793) and correlation between genetic distance and geographic distance matrices (r = 0.5638, P > 0.5) indicated that, there was no significant geographic heterogeneity among these populations.Key words: Pomacea canaliculata, inter simple sequence repeat (ISSR), genetic diversity, geographical populations

Exploring multipartite quantum correlations with the square of quantum discord

We explore the quantum correlation distribution in multipartite quantum states based on the square of quantum discord (SQD). For tripartite quantum systems, we derive the necessary and sufficient condition for the SQD to satisfy the monogamy relation. Particularly, we prove that the SQD is monogamous for three-qubit pure states, based on which a genuine tripartite quantum correlation measure is introduced. In addition, we also address the quantum correlation distributions in four-qubit pure states. As an example, we investigate multipartite quantum correlations in the dynamical evolution of multipartite cavity-reservoir systems.Comment: 8 pages, 5 figure

Effect of nitrogen fertilization on net nitrogen mineralization in grassland soil of Northern China: implications for grassland management

Nitrogen (N) applications can have a significant effect on soil N availability. The effect of 3 years of N fertilization on soil net N mineralization during the growing season (May–September) was studied in 2005 and 2006 in grassland of northern China. The experimental design was a randomized complete block with four replications of five rates of N addition as urea (0, 2, 4, 8 and 16 g N m−2 year−1). Results indicated that net N mineralization rate varied seasonally and between years, ranging from −0.04 to 0.52 μg g−1 d−1 in 2005 and from −0.09 to 0.39 μg g−1 d−1 in 2006. Mean N mineralization and nitrification rates were highest in July, in 2005 and 2006, whereas highest ammonification rates occurred in September. Rainfall was significantly correlated with net nitrification. In comparison with the untreated control, N mineralization increased sharply when N fertilization increased from 2 to 8 g N m−2 year−1. Mobile soil NO3− accumulated late in the growing season for the 16 g N m−2 year−1 treatment, suggesting the potential for NO3 and associated cation leaching. These results suggest that N fertilization of 8 g N m−2 year−1 (80 kg N ha−1) is suitable for the management of grassland ecosystems of Inner Mongolia