Predicting the impact of research institutions is an important tool for decision makers, such as resource allocation for funding bodies. Despite significant effort of adopting quantitative indicators to measure the impact of research institutions, little is known that how the impact of institutions evolves in time. Previous studies have focused on using the historical relevance scores of different institutions to predict potential future impact for these institutions. In this paper, we explore the factors that can drive the changes of the impact of institutions, finding that the impact of an institution, as measured by the number of the accepted papers of the institution, more is determined by the authors' influence of the institution. Geographic location of institution feature and state GDP can drive the changes of the impact of institutions. Identifying these features allows us to formulate a predictive model that integrates the effects of individual ability, location of institution, and state GDP. The model unveils the underlying factors driving the future impact of institutions, which can be used to accurately predict the future impact of institutions.

Spatial distribution of drought plays key role specifically in hydrological research. Drought is a complex stochastic natural hazard caused by prolonging shortage of rainfall and available water resources. The multi-scalar drought indices (based on probability distribution) are commonly used for making effective drought mitigation policies. In addition, the multi-scalar drought indices have great extent of the inaccurate determination of drought classes due to its probabilistic nature. However, the interpretation and applicability of various time scales are cumbersome for multi-scalar drought in various meteorological stations at a particular region. In this regards, accurate estimation and continuous monitoring of future drought at regional level requires a more appropriate and important time scale with respect to regions under study. In this study, we aimed to investigate the appropriate time scale for multi-scalar drought indices by using geo-reference points of meteorological stations. We used Boruta algorithm with two random forest adapters of machine learning algorithms for regionalized optimization of drought monitoring time scale. We explored the appropriate time scale for the Standardized Precipitation Temperature Index (SPTI) of 52 meteorological stations that are located across Pakistan. Results show that the significant importance of SPTI-1 (1-month time scale) for further spatial and temporal studies. That is, being high ranked and prominence, SPTI-1 has the ability to capture the characteristics of all other time scales that are in some circumstances applicable for drought characterization and classification.

Citation is a universally acknowledged way for scientific impact evaluation. However, due to its easy manipulability, simply relying on citation cannot objectively reflect the actual impact of scholars. Instead of citation, we utilize the academic networks, in virtue of their available and abundant academic information, to evaluate the scientific impact of scholars in this paper. Through the collaboration among scholars in academic networks, we notice an interesting phenomenon that scholars in some special positions can access more kinds of information and connect researchers from different groups to promote the scientific collaborations. However, this important fact is generally ignored by the existing approaches. Motivated by the observations above, we propose the novel method AIRank to evaluate the scientific impact of scholars. Our method not only considers the impact of scholars through the mutual reinforcement process in heterogeneous academic networks, but also integrates the structural holes theory and information entropy theory to depict the benefit that scholars obtain via their positions in the network. The experimental results demonstrate the effectiveness of AIRank in evaluating the impact of scholars more comprehensively and finding more top ranking scholars with interdisciplinary nature.