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Physiological and haplogroup studies performed to understand high-altitude adaptation in humans are limited to individual genes and polymorphic sites. Due to stochastic evolutionary forces, the frequency of a polymorphism is affected by changes in the frequency of a near-by polymorphism on the same DNA sample making them connected in terms of evolution. Here, first, we provide a method to model these mitochondrial polymorphisms as “co-mutation networks” for three high-altitude populations, Tibetan, Ethiopian and Andean. Then, by transforming these co-mutation networks into weighted and undirected gene–gene interaction (GGI) networks, we were able to identify functionally enriched genetic interactions of CYB and CO3 genes in Tibetan and Andean populations, while NADH dehydrogenase genes in the Ethiopian population playing a significant role in high altitude adaptation. These co-mutation based genetic networks provide insights into the role of different set of genes in high-altitude adaptation in human sub-populations.

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The distribution of the ratios of consecutive eigenvalue spacings of random matrices has emerged as an important tool to study spectral properties of many-body systems. This article numerically investigates the eigenvalue ratios distribution of various model networks, namely, small-world, Erdős-Rényi random, and (dis)assortative random having a diagonal disorder in the corresponding adjacency matrices. Without any diagonal disorder, the eigenvalues ratio distribution of these model networks depict Gaussian orthogonal ensemble (GOE) statistics. Upon adding diagonal disorder, there exists a gradual transition from the GOE to Poisson statistics depending upon the strength of the disorder. The critical disorder (wc) required to procure the Poisson statistics increases with the randomness in the network architecture. We relate wc with the time taken by maximum entropy random walker to reach the steady-state. These analyses will be helpful to understand the role of eigenvalues other than the principal one for various network dynamics such as transient behaviour.

This paper provides an overview of the increasing R&D activity in metal matrix composites worldwide, with a particular focus on cast particulate metal matrix composites. Large-scale applications of cast aluminum alloy MMCs in everyday use in the transportation and consumer durables industries are expected to advance rapidly over the next decade. India has great potential for widespread application of cast composites, especially in the fields of transportation, energy and electrical machinery. Widespread use of composites can result in significant material and energy savings and, in some cases, reduced pollution. It is important to organize engineering education and short courses to make students and engineering professionals aware of his MMC. India already has an excellent infrastructure for composites development and a long track record of world-class cast metal matrix composites research. Today there is a need to catalyze prototypes and series production of selected composite components and use them in various sectors, especially in railways, cars, trucks, buses, scooters and other electrical machines. This requires a well-funded strategy to bring together the world-class foundry composites talent already present in India to form a viable development group. We will then establish a manufacturing facility that incorporates the process engineering capabilities that already exist in the country. Cast composites must be developed for use in power generation equipment, aerospace electronic packaging systems, and smart structures.