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A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein-protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein-protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.

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In Brazil, rice production is predominantly concentrated in the South region, employing a continuous flood irrigation system throughout the crop cycle. However, this irrigation management strategy in the tropical region contributes to low water‐use efficiency owing to adverse climatic conditions. Furthermore, with climate change projections indicating reduced water availability, the study aims to investigate the impact of alternative irrigation management strategies on the phenological development, gas exchange, biomass accumulation, and productivity of tropical irrigated rice. Three alternative irrigation management approaches—intermittent flood irrigation with aeration (IFA), intermittent flood irrigation throughout the growth cycle (IFC), and intermittent flooding up to the flowering stage (IFF)—were compared with the traditional continuous flood irrigation throughout the growth cycle. Phenological data, gas exchange, growth, and productivity dynamics were subject to analysis, providing overarching insights into management practices. Notably, irrigation management exhibited no influence on the vegetative phase of the crop. The implementation of intermittent flood irrigation facilitated a reduction in water supply without compromising the physiological performance of tropical irrigated rice. Strategies promoting judicious water utilization, such as IFA and IFC, can be readily integrated into the cultivation of tropical irrigated rice without detriment to grain yield or harvest index. Core Ideas: Intermittent flood irrigation does not compromise the physiology of tropical irrigated rice.Irrigation management does not affect the vegetative development of tropical irrigated rice.Strategies that rationalize water use do not compromise grain yield and harvest index. [ABSTRACT FROM AUTHOR]

This work applies different numerical methods involved in the solution of a nonlinear clamped beam problem. The methodology used in the discretization of the dynamic problem is based on the Finite Element Method (FEM), followed by mode superposition, where a localized nonlinearity is applied at the free end of the beam. The solution of the nonlinear problem is performed by five different integration methods. The solution code is implemented in FORTRAN language, validated with ANSYS and the dynamic response and the graphs are obtained with the help of MATLAB software. The work shows the convergence of the implemented methods with various validation problems.