5.5/10 Best for: Nostalgic PC shooter fans, mission editor hobbyists, and anyone who misses NovaLogic’s unique brand of military simulation.
Here’s a write-up for Delta Force: Xtreme 2 , covering its background, gameplay, strengths, and weaknesses. Released in 2009 by NovaLogic, Delta Force: Xtreme 2 (DFX2) arrived as a belated sequel to the 2005 Delta Force: Xtreme , which itself was an updated version of the classic Delta Force: Black Hawk Down and Team Sabre . In an era dominated by Call of Duty and Battlefield , DFX2 attempted to recapture the magic of late-90s and early-2000s tactical shooters — with mixed results. Gameplay & Features At its core, DFX2 stays true to the Delta Force formula: large, open-ended maps, realistic ballistics (bullet drop and travel time), and a focus on long-range engagement. Unlike modern hitscan shooters, players must lead their targets and account for gravity, which rewards patience and skill.
install.packages(repos=c(FLR="https://flr.r-universe.dev", CRAN="https://cloud.r-project.org"))
5.5/10 Best for: Nostalgic PC shooter fans, mission editor hobbyists, and anyone who misses NovaLogic’s unique brand of military simulation.
Here’s a write-up for Delta Force: Xtreme 2 , covering its background, gameplay, strengths, and weaknesses. Released in 2009 by NovaLogic, Delta Force: Xtreme 2 (DFX2) arrived as a belated sequel to the 2005 Delta Force: Xtreme , which itself was an updated version of the classic Delta Force: Black Hawk Down and Team Sabre . In an era dominated by Call of Duty and Battlefield , DFX2 attempted to recapture the magic of late-90s and early-2000s tactical shooters — with mixed results. Gameplay & Features At its core, DFX2 stays true to the Delta Force formula: large, open-ended maps, realistic ballistics (bullet drop and travel time), and a focus on long-range engagement. Unlike modern hitscan shooters, players must lead their targets and account for gravity, which rewards patience and skill. delta force: xtreme 2
The FLR project has been developing and providing fishery scientists with a powerful and flexible platform for quantitative fisheries science based on the R statistical language. The guiding principles of FLR are openness, through community involvement and the open source ethos, flexibility, through a design that does not constraint the user to a given paradigm, and extendibility, by the provision of tools that are ready to be personalized and adapted. The main aim is to generalize the use of good quality, open source, flexible software in all areas of quantitative fisheries research and management advice.
Development code for FLR packages is available both on Github and on R-Universe. Bugs can be reported on Github as well as suggestions for further development.
Studies and publications citing or using FLR
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Please submit an issue for the relevant package, or at the tutorials repository.
