A clear, data-focused look at how GA4 Attribution Paths help advertisers validate Smart Bidding, prove assist value, and defend upper-funnel spend. Let’s state a fact: Google Ads in 2025 runs on ...

1 Department of Hydraulics, Sanitary Environmental Protection, Faculty of Hydrotechnics, Technical University of Civil Engineering of Bucharest, Bucharest, Romania. 2 Department of Hydraulics, ...

Immunotherapy has emerged as a powerful approach in treating various diseases, yet its success often hinges on the efficacy of adjuvants, agents that boost immune responses to therapeutic targets.

When it comes to digital advertising, understanding how different touchpoints contribute to conversions is key to maximizing your return on investment (ROI). Traditional attribution models, like first ...

The role of Artificial Intelligence (AI) in managing game difficulty is significantly increasing as players are now after more personalized and engaging gaming experiences. Dynamic Difficulty ...

Proteomic workflows generate vastly complex peptide mixtures that are analyzed by liquid chromatography–tandem mass spectrometry, creating thousands of spectra, most of which are chimeric and contain ...

This is an ongoing project where I'm trying to make a performant voxel rendering engine using C++ and Vulkan. Compute shader which runs at half screen resolution. Marches rays through octree chunks ...

Although data-independent acquisition (DIA) shows powerful potential in achieving comprehensive peptide information acquisition, the difficulty in determining the precursor m/z and distinguishing ...

During the last few years we have spoken to a long list of businesses around the world who are spending more than $100k/month advertising their products on Facebook. When discussing their results, ...

Scientists have developed a novel approach for dynamic difficulty adjustment where the players' emotions are estimated using in-game data, and the difficulty level is tweaked accordingly to maximize ...

We propose a direct domain adaptation (DDA) approach to enrich the training of supervised neural networks on synthetic data by features from real-world data. The process involves a series of linear ...