Trajectory-based global sensitivity analysis in multiscale models.

This research introduces a novel global sensitivity analysis (GSA) framework for agent-based models (ABMs) that explicitly handles their distinctive features, such as multi-level structure and temporal dynamics. The framework uses Grassmannian diffusion maps to reduce output data dimensionality and sparse polynomial chaos expansion (PCE) to compute sensitivity indices for stochastic input parameters. To demonstrate the versatility of the proposed GSA method, we applied it to a non-linear system dynamics model and epidemiological and economic ABMs, depicting different dynamics. Unlike traditional GSA approaches, the proposed method enables a more general estimation of parametric sensitivities spanning from the micro level (individual agents) to the macro level (entire population). The new framework encourages the use of manifold-based techniques in uncertainty quantification, enhances understanding of complex spatio-temporal processes, and equips ABM practitioners with robust tools for detailed model analysis. This empowers them to make more informed decisions when developing, fine-tuning, and verifying models, thereby advancing the field and improving routine practice for GSA in ABMs.

Aminoacyl-tRNA Synthetases, Indispensable Players in Lung Tumorigenesis.

Being an essential enzyme in protein synthesis, the aminoacyl-tRNA synthetases (aaRSs) have a conserved function throughout evolution. However, research has uncovered altered expressions as well as interactions of aaRSs, in league with aaRS-interacting multi-functional proteins (AIMPs), forming a multi-tRNA synthetase complex (MSC) and divulging into their roles outside the range of protein synthesis. In this review, we have directed our focus into the rudimentary structure of this compact association and also how these aaRSs and AIMPs are involved in the maintenance and progression of lung cancer, the principal cause of most cancer-related deaths. There is substantial validation that suggests the crucial role of these prime housekeeping proteins in lung cancer regulation. Here, we have addressed the biological role that the three AIMPs and the aaRSs play in tumorigenesis, along with an outline of the different molecular mechanisms involved in the same. In conclusion, we have introduced the potentiality of these components as possible therapeutics for the evolution of new-age treatments of lung tumorigenesis.

Survey-based socio-economic data from slums in Bangalore, India.

In 2010, an estimated 860 million people were living in slums worldwide, with around 60 million added to the slum population between 2000 and 2010. In 2011, 200 million people in urban Indian households were considered to live in slums. In order to address and create slum development programmes and poverty alleviation methods, it is necessary to understand the needs of these communities. Therefore, we require data with high granularity in the Indian context. Unfortunately, there is a paucity of highly granular data at the level of individual slums. We collected the data presented in this paper in partnership with the slum dwellers in order to overcome the challenges such as validity and efficacy of self reported data. Our survey of Bangalore covered 36 slums across the city. The slums were chosen based on stratification criteria, which included geographical location of the slum, whether the slum was resettled or rehabilitated, notification status of the slum, the size of the slum and the religious profile. This paper describes the relational model of the slum dataset, the variables in the dataset, the variables constructed for analysis and the issues identified with the dataset. The data collected includes around 267,894 data points spread over 242 questions for 1,107 households. The dataset can facilitate interdisciplinary research on spatial and temporal dynamics of urban poverty and well-being in the context of rapid urbanization of cities in developing countries.