Rural tourism plays a crucial role in rural development in Indonesia by providing employment opportunities, livelihood, infrastructure, cultural preservation, and environmental preservation. However, it is prone to external shocks such as natural disasters, public health events, and volatility in the national and global economy. This study measures the resilience of rural tourism to external shocks caused by the COVID-19 pandemic in 24 rural tourism destinations in Indonesia covering four years from 2019 to 2022. A synthetic composite index of the Adjusted Mazziotta-Pareto index (AMPI) is used to measure rural tourism resilience followed by clustering analysis to determine the typology of the resilience. The AMPI measure is also compared with the conventional Mazziotta-Pareto index (MPI) method. The resilience index is composed of capacity and performance components related to resilience. The results show that in the first year of COVID-19, most tourism villages in Indonesia were severely affected by the pandemic, yet they were able to recover afterward, as indicated by positive differences in the AMPI index before and after COVID-19. Thus, rural tourism villages in Indonesia have a strong capacity and performance to recover from pandemic shock. Lessons learned from this analysis can be applied to policies related to rural tourism resilience in developing countries.

In order to scientifically evaluate the germplasm resources of Momordica charantia in southern China, the diversity, correlation and cluster analysis were carried out on the main botanical characters of 56 Momordica charantia varieties, such as melon length, melon transverse diameter, single melon weight, internode length, stem diameter, leaf length and leaf width. The results showed that the variation coefficients of 7 agronomic characters of 56 Momordica charantia varieties ranged from 8.81% to 19.44%, the average variation coefficient was 14.21%, the maximum variation coefficient of single melon weight was 19.44%, and the minimum variation coefficient of melon cross diameter was 8.81%. The correlation analysis showed that there were correlations among the agronomic traits. The positive correlation coefficient between leaf length and leaf width was up to 0.978, and the negative correlation coefficient between single melon weight and internode length was up to 0.451. The 56 varieties were divided into 3 groups by cluster analysis, of which 92.86% of the materials were concentrated in the first and second groups, and there were only 4 materials in the third group. The results can provide a reference for the cultivation, utilization and genetic improvement of Momordica charantia resources in southern China.

Theoretically, within the diatomic model, the relative stability of most abundant boron clusters B₁₁, B₁₂, and B₁₃ with planar structures in neutral, positive and negative charged-states is studied. According to the specific (per atom) binding energy criterion, B₁₂⁺ (6.49 eV) is found to be the most stable boron cluster, while B₁₁^– + B₁₃⁺ (5.83 eV) neutral pair is expected to present the preferable ablation channel for boron-rich solids. Obtained results would be applicable in production of boron-clusters-based nanostructured coating materials with super-properties such as lightness, hardness, conductivity, chemical inertness, neutron-absorption, etc., making them especially effective for protection against cracking, wear, corrosion, neutron- and electromagnetic-radiations, etc.

This article describes a classification tool to cluster SARAL/AltiKa waveforms. The tool was made using Python scripts. Radar altimetry systems (e.g., SARAL/AltiKa) measures the distance from the satellite centre to a target surface by calculating the satellite-to-surface round-trip time of a radar pulse. An altimeter waveform represents the energy reflected by the earth’s surface to the satellite antenna with respect to time. The tool clusters the altimetric waveforms data into desired groups. For the clustering, we used evolutionary minimize indexing function (EMIF) with k-means cluster mechanism. The idea was to develop a simple interface which takes the altimetry waveforms data from a folder as inputs and provides single value (using EMIF algorithm) for each waveform. These values are further used for clustering. This is a simple light weighted tool and user can easily interact with it.