Pollutant metal ions detection and preparation of water-soluble fluorescent polymeric particles

Funding Information: G.D. thanks to the European Regional Development Fund within the Operational Programme Science and Education for Smart Growth 2014–2020 under the Project Center of Exellence: National center of mechatronics and clean technologies - BG05M2OP001-1.001-0008 for the financial support. Funding Information: This work was supported by the Associate Laboratory for Green Chemistry - LAQV which is financed by national funds from FCT/MCTES ( UIDB/50006/2020 and UIDP/50006/2020 ) as well as the PROTEOMASS Scientific Society (Portugal) for funding support (General Funding Grant 2022–2023). F.D. thanks to FCT / MEC (Portugal) for his doctoral grant 2021.05161.BD . E.O thanks FCT / MEC (Portugal) for the individual contract, CEECIND/00648/2017. J.F-.L. thanks the FCT / MEC (Portugal) for the individual research contract DL57. HMS acknowledges the Associate Laboratory for Green Chemistry-LAQV ( LA/P/0008/2020 ) funded by FCT / MCTES for his research contract. Funding Information: The financial support by the Bulgarian National Science Fund (BNSF) under grant – “Novel styryl and polymethine fluorophores as potential theranostic agents “contract N◦ КП-06-М59/1 from 15.11.2021 is gratefully acknowledged by A.K. This work is also developed and acknowledged by A.K. as part of contract №: BG-RRP-2.004-0002-C01, Laboratory of Organic Functional Materials (Project BiOrgaMCT), Procedure BG-RRP-2.004, Establishing of a network of research higher education institutions in Bulgaria”, funded by BULGARIAN NATIONAL RECOVERY AND RESILIENCE PLAN ”. Publisher Copyright: © 2023 The AuthorsPolarity-sensitive dansyl derivatives L1 and L2 were synthesized and their ability to sense pollutant metal ions was investigated. All compounds were found to be highly sensitive towards Cu2+ and Hg2+ metal ions, while L2 being able to detect and quantify Hg2+ concentrations as low as 2.5 μM. Both L1 and L2 exhibit positive solvatofluorochromic behaviour, modulated in the presence of water, which in turn results in fluorescence enhancement via aggregation-induced emission (AIE). Seeking stability and water solubility, luminescent L1-based polystyrene-block-polybutadiene-block-polystyrene (SBS) microparticles (size: 520 ± 76 nm) were successfully prepared while maintaining the fluorescence emission of fluorophore L1 (φ = 22%). This work exemplifies the multiple properties of dansyl-derivatives and their promising applications in biomedicine and environmental fields.publishersversionpublishe

New Physics Agnostic Selections For New Physics Searches

We discuss a model-independent strategy for boosting new physics searches with the help of an unsupervised anomaly detection algorithm. Prior to a search, each input event is preprocessed by the algorithm - a variational autoencoder (VAE). Based on the loss assigned to each event, input data can be split into a background control sample and a signal enriched sample. Following this strategy, one can enhance the sensitivity to new physics with no assumption on the underlying new physics signature. Our results show that a typical BSM search on the signal enriched group is more sensitive than an equivalent search on the original dataset

Interaction networks for the identification of boosted H→bb‾H\to b\overline{b} decays

We develop an algorithm based on an interaction network to identify high-transverse-momentum Higgs bosons decaying to bottom quark-antiquark pairs and distinguish them from ordinary jets that reflect the configurations of quarks and gluons at short distances. The algorithm's inputs are features of the reconstructed charged particles in a jet and the secondary vertices associated with them. Describing the jet shower as a combination of particle-to-particle and particle-to-vertex interactions, the model is trained to learn a jet representation on which the classification problem is optimized. The algorithm is trained on simulated samples of realistic LHC collisions, released by the CMS Collaboration on the CERN Open Data Portal. The interaction network achieves a drastic improvement in the identification performance with respect to state-of-the-art algorithms.Comment: 20 pages, 8 figures, 6 tables, version published in PR