PENGELOMPOKAN TITIK GEMPA DI PULAU SULAWESI MENGGUNAKAN ALGORITMA ST-DBSCAN (Spatio Temporal-Density Based Spatial Clustering Application with Noise)

Earthquake is a natural disaster which is quite serious in Indonesia, especially on Sulawesi Island. Earthquake is fearful because it can’t be predicted when it will come, where it will come, and how strong the vibration, that often causes fatal damage and casualties. In effort to minimize losses caused by earthquake, it is necessary to divide areas which are easily affected by earthquake. One of the methods that can be used in dividing the area is by using the clustering technique. This research by using a clustering method with the ST-DBSCAN (Spatial Temporal-Density Based Spatial Clustering Application with Noise) algorithm on dataset of earthquake points in Sulawesi Island in 2019. This method by using the spatial distance parameters (Eps1 = 0.45), the temporal distance parameters (Eps2 = 7), and minimum number of cluster members (MinPts = 4), resulting in a total of 60 clusters with 8 large clusters and 216 noises

Theoretical studies on the two-photon absorption of II–VI semiconductor nano clusters

Semiconductor clusters, ZnnOn, ZnnSn, and CdnSn (n = 2–8), were optimized and the corresponding stable structures were acquired. The symmetry, bond length, bond angle, and energy gap between HOMO and LUMO were analyzed. According to reasonable calculation and comparative analysis for small clusters Zn2O2, Zn2S2, and Cd2S2, an effective method based on density function theory (DFT) and basis set which lay the foundation for the calculation of the large clusters have been obtained. The two-photon absorption (TPA) results show that for the nano clusters with planar configuration, sizes play important role on the TPA cross section, while symmetries determine the TPA cross section under circumstance of 3D stable structures. All our conclusions provide theoretical support for the development of related experiments.

Quasi-isotropic SMMs: slow relaxation of the magnetization in polynuclear CuII/MnII complexes.

Three field induced SMMs built from quasi isotropic cations like CuII and MnII have been characterized, showing that relatively large clusters with quasi negligible D and different ground spin state,...

Worldwide clustering and infection cycles as universal features of multiscale stochastic processes in the SARS-CoV-2 pandemic

Predicting the evolution of the current epidemic depends significantly on understanding the nature of the underlying stochastic processes. To unravel the global features of these processes, we analyse the world data of SARS-CoV-2 infection events, scrutinising two eight-month periods associated with the epidemic's outbreak and initial immunisation phase. Based on the correlation-network mapping, K-means clustering, and multifractal time series analysis, our results reveal universal patterns, suggesting potential predominant drivers of the pandemic. More precisely, the Laplacian eigenvectors localisation has revealed robust communities of different countries and regions that then cluster according to similar shapes of infection fluctuations. Apart from quantitative measures, the immunisation phase differs significantly from the epidemic outbreak by the countries and regions constituting each cluster. While the similarity grouping possesses some regional components, the appearance of large clusters spanning different geographic locations is persevering. Furthermore, cyclic trends are characteristic of the identified clusters, dominating large temporal fluctuations of infection evolution, which are prominent in the immunisation phase. Meanwhile, persistent fluctuations around the local trend occur in intervals smaller than 14 days. These results provide a basis for further research into the interplay between biological and social factors as the primary cause of infection cycles and a better understanding of the impact of socio-economical and environmental factors at different phases of the pandemic.

Worldwide clustering and infection cycles as universal features of multiscale stochastic processes in the SARS-CoV-2 pandemic

Predicting the evolution of the current epidemic depends significantly on understanding the nature of the underlying stochastic processes. To unravel the global features of these processes, we analyse the world data of SARS-CoV-2 infection events, scrutinising two eight-month periods associated with the epidemic’s outbreak and initial immunisation phase. Based on the correlation-network mapping, K-means clustering, and multifractal time series analysis, our results reveal universal patterns, suggesting potential predominant drivers of the pandemic. More precisely, the Laplacian eigenvectors localisation has revealed robust communities of different countries and regions that then cluster according to similar shapes of infection fluctuations. Apart from quantitative measures, the immunisation phase differs significantly from the epidemic outbreak by the countries and regions constituting each cluster. While the similarity grouping possesses some regional components, the appearance of large clusters spanning different geographic locations is persevering. Furthermore, cyclic trends are characteristic of the identified clusters, dominating large temporal fluctuations of infection evolution, which are prominent in the immunisation phase. Meanwhile, persistent fluctuations around the local trend occur in intervals smaller than 14 days. These results provide a basis for further research into the interplay between biological and social factors as the primary cause of infection cycles and a better understanding of the impact of socio-economical and environmental factors at different phases of the pandemic.

Chemistry-Mediated Ostwald Ripening in Carbon-Rich C/O Systems at Extreme Conditions

There is significant interest in establishing a capability for tailored synthesis of next-generation carbon-based nanomaterials due to their broad range of applications and high degree of tunability. High pressure (e.g. shockwave-driven) synthesis holds promise as an effective discovery method, but experimental challenges preclude elucidating the processes governing nanocarbon production from carbon-rich precursors that could otherwise guide efforts through the prohibitively expansive design space. Here we report findings from large scale atomistically-resolved simulations of carbon condensation from C/O mixtures subjected to extreme pressures and temperatures, made possible by machine-learned reactive interatomic potentials. We find that liquid nanocarbon formation follows classical growth kinetics driven by Ostwald ripening (i.e. growth of large clusters at the expense of shrinking small ones) and obeys dynamical scaling in a process mediated by carbon chemistry in the surrounding reactive fluid. The results provide direct insight into carbon condensation in a representative system and pave the way for its exploration in higher complexity organic materials. They also suggest that simulations using machine-learned interatomic potentials could eventually be employed as in-silico design tools for new nanomaterials.

Status and life strategy of Orchis punctulata Steven ex Lindl. (Orchidaceae) in the South-Eastern Crimea

This article presents the results of the population studies of rare protected species Orchis punctulata (Orchidaceae). Based on analysis of local floras in eastern and southeastern Crimea and personal observations, we identified the three most numerous populations of O. punctulata: two in the steppe (on the Tepe-Oba mountain ridge) and one in forest communities (on the Kiziltash mountain ridge). The ontogenetic, demographic, and vitality structures of the populations were studied. We also assessed the life strategies of the species in different habitats. The populations in steppe communities were characterized by high number and density parameters. O. punctulate often formed large clusters and was dominated here. A small number and low density characterized the population in the forest community; the distribution of individuals within the population was scattered. The age spectra were also different. The populations in steppe communities had a left-sided spectrum with a maximum in immature individuals, while in forest communities, it had a bimodal spectrum with maximums in generative (with a predominance of mature and old generative) and immature individuals. Specimens from forest communities were more extensive than those of steppe communities, they had longer leaves and inflorescences, and their inflorescences had a more significant number of flowers. As a result, the population in the forest community had a higher vitality index. It included individuals of the highest and middle class of vitality. The populations in the steppe community consisted of all classes of vitality or only of middle and lower classes. Thus, optimal environmental conditions for the growth of species are in forests. At the same time, a low level of regeneration and competition from other plants hinder its wide distribution. As a result, the species exserts as a phytocenotic patient (S-strategy). In steppe communities, the species is characterized by a mixed patient-explerant-violant strategy (SRC strategy).

Experiment study on the corrosion resistance of the surface metamorphic layer of grinding

Workpiece will face corrosive problems during its application after the manufacturing process. As the common final process, grinding can generate special metamorphic layer on the surface of workpiece and change the initial corrosion resistance of workpiece. In order to study the corrosion resistance of workpiece after grinding process, the paper carries on combining experiment of grinding and electrochemical corrosion. The characteristic of corrosion resistance of grinding is revealed based on the association of grinding mechanism and electrochemical theory. The corrosion potential of workpiece after grinding is higher than matrix, which shows the grinding surface is difficult to begin to corrode. Electrochemical impedance spectroscopy (EIS) shows the grinding surface has large phase angle, impedance and capacitance characteristic because the metamorphic layer of grinding has good obstructive ability. They reveal that grinding improves the surface corrosion resistance of workpiece. Then the mechanism of the corrosion resistance of grinding is revealed. The special grain boundary formed in grinding with much C element, large clusters and complex shape prolongs the corrosion channel, which reduces the corrosive speed. While, the sensitive hardening structure generated in grinding hardening with much free energy is easy to form the corrosion cell, which will accelerate the corrosion.

NASA’s Lucy mission launches to Jupiter’s Trojan asteroids

NASA has launched a $1bn mission to study Jupiter’s Trojan asteroids – two large clusters of rocks that are believed to be remnants of primordial material that formed the solar system’s outer planets.

The Effect of Ultra Fine Bubbles Water on the Human skin

A certain amount of water needs to be maintained in the stratum corneum of the skin in order to maintain the skin barrier function. Therefore, it is important to supply water to the stratum corneum of the skin to reduce trans epidermal water loss (TEWL). However, because normal water has large clusters, it is difficult to penetrate the stratum corneum of the skin. Therefore, it was considered that the use of Ultra-fine bubbles (UFB) water, which is said to have small water clusters, promotes penetration into the stratum corneum of the skin, and is useful for improving the skin barrier function. The artificial skin to which O2-UFB water was dripped had the highest water content and the lowest TEWL. It also had a high affinity for human skin. From these results, improvement of skin barrier function by O2-UFB water can be expected.