Significant advances in deep learning have led to more widely used and precise neural network-based generative models such as Generative Adversarial Networks (Gans). We introduce a post-hoc correction to deep generative models to further improve their fidelity, based on the Deep neural networks using the Classification for Tuning and Reweighting (Dctr) protocol. The correction takes the form of a reweighting function that can be applied to generated examples when making predictions from the simulation. We illustrate this approach using Gans trained on standard multimodal probability densities as well as calorimeter simulations from high energy physics. We show that the weighted Gan examples significantly improve the accuracy of the generated samples without a large loss in statistical power. This approach could be applied to any generative model and is a promising refinement method for high energy physics applications and beyond.

BACKGROUND AND AIMS: Heparin-binding EGF-like growth factor (HB-EGF) is a representative EGF family member that interacts with EGFR under diverse stress environment. Previously, we reported that the HB-EGF-targeting using antisense oligonucleotide (ASO) effectively suppressed an aortic aneurysm in the vessel wall and circulatory lipid levels. In this study, we further examined the effects of the HB-EGF ASO administration on the development of hyperlipidemia-associated atherosclerosis using an atherogenic mouse model. METHODS AND RESULTS: The male and female LDLR deficient mice under Western diet containing 21% fat and 0.2% cholesterol content were cotreated with control and HB-EGF ASOs for 12 weeks. We observed that the HB-EGF ASO administration effectively downregulated circulatory VLDL- and LDL-associated lipid levels in circulation; concordantly, the HB-EGF targeting effectively suppressed the development of atherosclerosis in the aorta. An EGFR blocker BIBX1382 administration suppressed the hepatic TG secretion rate, suggesting a positive role of the HB-EGF signaling for the hepatic VLDL production. We newly observed that there was a significant improvement of the insulin sensitivity by the HB-EGF ASO administration in a mouse model under the Western diet as demonstrated by the improvement of the glucose and insulin tolerances. CONCLUSION: The HB-EGF ASO administration effectively downregulated circulatory lipid levels by suppressing hepatic VLDL production rate, which leads to effective protection against atherosclerosis in the vascular wall.

The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the AI4EIC working group, which recently took place, centered on exploring all current and prospective application areas of AI for the EIC. This workshop is not only beneficial for the EIC, but also provides valuable insights for the newly established ePIC collaboration at EIC. This paper summarizes the different activities and R&D projects covered across the sessions of the workshop and provides an overview of the goals, approaches and strategies regarding AI/ML in the EIC community, as well as cutting-edge techniques currently studied in other experiments.

Motivated by the success of the flavour physics programme carried out over the last decade at the Large Hadron Collider (LHC), we characterize in detail the physics potential of its High-Luminosity and High-Energy upgrades in this domain of physics. We document the extraordinary breadth of the HL/HE-LHC programme enabled by a putative Upgrade II of the dedicated flavour physics experiment LHCb and the evolution of the established flavour physics role of the ATLAS and CMS general purpose experiments. We connect the dedicated flavour physics programme to studies of the top quark, Higgs boson, and direct high-$p_T$ searches for new particles and force carriers. We discuss the complementarity of their discovery potential for physics beyond the Standard Model, affirming the necessity to fully exploit the LHC's flavour physics potential throughout its upgrade eras.

The Belle II detector will provide a major step forward in precision heavy flavor physics, quarkonium and exotic states, searches for dark sectors, and many other areas. The sensitivity to a large number of key observables can be improved by about an order of magnitude compared to the current measurements, and up to two orders in very clean search measurements. This increase in statistical precision arises not only due to the increased luminosity, but also from improved detector efficiency and precision for many channels. Many of the most interesting observables tend to have very small theoretical uncertainties that will therefore not limit the physics reach. This book has presented many new ideas for measurements, both to elucidate the nature of current anomalies seen in flavor, and to search for new phenomena in a plethora of observables that will become accessible with the Belle II dataset. The simulation used for the studiesinthis book was state ofthe artat the time, though weare learning a lot more about the experiment during the commissioning period. The detector is in operation, and working spectacularly well.