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In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
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Background: ISG15 is an Ubiquitin-like protein, highly induced by Type I Interferons. Upon the cooperative activity of specific Ubiquitinating enzymes, ISG15 can be conjugated to its substrates. Increasing evidence points to a role for protein ISGylation in anti-viral and anti-tumoral defense. Principal Findings: We identified ISG15 from Old World Monkeys (OWm) as a hyper-efficient protein modifier. Western blot analysis visualized more efficient conjugation of OWmISG15 relative to HuISG15 in human (Hu), monkey and mouse (Mo) cell-lines. Moreover, the substrates of OWmISG15 identified upon Tandem Affinity Purification followed by LC-MS/MS identification largely outnumbered these of HuISG15 itself. Several Ubiquitin-Conjugating enzymes were identified as novel ISGylated substrates. Introduction of a N89D mutation in HuISG15 improved its ISGylation capacity, and additional Q31K/ T33A/D133N mutations yielded a HuISG15 variant with an ISGylation efficiency comparable to OWmISG15. Homology modeling and structural superposition situate N89 in the interaction interface with the Activating enzyme. Analysis of the UbE1L residues in this interface revealed a striking homology between OWmUbE1L and HuUbE1, the Activating enzyme of Ubiquitin. In line with this observation, we found efficient activation of AgmISG15, but not HuISG15 or MoISG15, by HuUbE1, thus providing a likely explanation for OWm hyperISGylation. Conclusions: This study discloses the poor conjugation competence of HuISG15 compared to OWmISG15 and maps the critical determinants for efficient conjugation. HyperISGylation may greatly assist ISGylation studies and may enhance its function as positive regulator of Interferon-related immune responses or as anti-tumoral modulator.
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HyperISGylation of Old World Monkey ISG15 in Human Cells

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Foot-and-mouth disease GIS OpenFOAM Livestock infectious diseases, such as foot-and-mouth disease (FMD), cause substantial economic damage to livestock farms and their related industries. Among various causes of disease spread, airborne dispersion has previously been considered to be an important factor that could not be controlled by preventive measures to stop the spread of disease that focus on direct and indirect contact. Forecasting and predicting airborne virus spread are important to make time for developing strategies and to minimise the damage of the disease. To predict the airborne spread of the disease a modelling approach is important since field experiments using sensors are ineffective because of the rarefied concentrations of virus in the air. The simulation of airborne spread during past outbreaks required improvement both for farmers and for policy decision makers. In this study a free license computational fluid dynamics (CFD) code was used to simulate airborne virus spread. Forecasting data from the Korea Meteorological Administration (KMA) was directly connected in the developed model for real-time forecasting for 48 h in three-hourly intervals. To reduce computation time, scalar transport for airborne virus spread was simulated based on a database for the CFD computed airflow in the investigated area using representative wind conditions. The simulation results, and the weather data were then used to make a database for a web-based forecasting system that could be accessible to users. ScienceDirect jo urnal homepage: www .e lsev ie r.com/ locate/issn/153 75110 b i o s y s t e m s e n g i n e e r i n g 1 2 9 ( 2 0 1 5 ) 1 6 9 e1 8 4 http://dx.
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Web-based forecasting system for the airborne spread of livestock infectious disease using computational fluid dynamics

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The relative motion of moving objects is an essential research topic in geographical information science (GIScience), which supports the innovation of geodatabases, spatial indexing, and geospatial services. This analysis is very popular in the domains of urban governance, transportation engineering, logistics and geospatial information services for individuals or industrials. Importantly, data models of moving objects are one of the most crucial approaches to support the analysis for dynamic relative motion between moving objects, even in the age of big data and cloud computing. Traditional geographic information systems (GIS) usually organize moving objects as point objects in absolute coordinated space. The derivation of relative motions among moving objects is not efficient because of the additional geo-computation of transformation between absolute space and relative space. Therefore, current GISs require an innovative approach to directly store, analyze and interpret the relative relationships of moving objects to support their efficient analysis. This paper proposes a relative space-based GIS data model of moving objects (RSMO) to construct, operate and analyze moving objects' relationships and introduces two algorithms (relationship querying and relative relationship dynamic pattern matching) to derive and analyze the dynamic relationships of moving objects. Three scenarios (epidemic spreading, tracker finding, and motion-trend derivation of nearby crowds) are implemented to demonstrate the feasibility of the proposed model. The experimental results indicates the execution times of the proposed model are approximately 5-50% those of the absolute GIS method for the same function of these three scenarios. It's better computational performance of the proposed model when analyzing the relative relationships of moving objects than the absolute methods in a famous commercial GIS software based on this experimental results. The proposed approach fills the gap of traditional GIS and shows promise for relative space-based geo-computation, analysis and service.
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ISPRS Journal of Photogrammetry and Remote Sensing Relative space-based GIS data model to analyze the group dynamics of moving objects