1. DECREMENTAL STRONGLY CONNECTED COMPONENTS AND SINGLE-SOURCE REACHABILITY IN NEAR-LINEAR TIME 

   Bernstein A.; Gutenberg M.P.; Wulff-Nilsen C. (2023)

   SIAM Journal on Computing

   Computing the strongly connected Components (SCCs) in a graph G = (V, E) is known to take only O(m+n) time using an algorithm by Tarjan [SIAM J. Comput., 1 (1972), pp. 146-160] where m = |E|, n = |V |. For fully dynamic graphs, conditional lower bounds provide evidence that the update time cannot be improved by polynomial factors over recomputing the SCCs from scratch after every update. Nevertheless, substantial progress has been made ...

   Journal Article

2. POLLUTION REGULATION FOR ELECTRICITY GENERATORS IN A TRANSMISSION NETWORK 

   Hernández-Santibáñez N.; Jofré A.; Possamaï D. (2023)

   SIAM Journal on Control and Optimization

   In this paper we study a pollution regulation problem in an electricity market with a network structure. The market is ruled by an independent system operator (ISO) who has the goal of reducing the pollutant emissions of the providers in the network by encouraging the use of cleaner technologies. The problem of the ISO formulates as a contracting problem with each one of the providers, who interact among themselves by playing a stochastic ...

   Journal Article

3. SUBWAVELENGTH RESONANCES IN ONE-DIMENSIONAL HIGH-CONTRAST ACOUSTIC MEDIA 

   Feppon F.; Cheng Z.; Ammari H. (2023)

   SIAM Journal on Applied Mathematics

   We propose a mathematical theory of acoustic wave scattering in one-dimensional finite high-contrast media. The system considered is constituted of a finite alternance of high-contrast segments of arbitrary lengths and interdistances, called the “resonators,” and a background medium. We prove the existence of subwavelength resonances, which are the counterparts of the well-known Minnaert resonances in three-dimensional systems. One of the ...

   Journal Article

4. Predicting Depression Risk in Patients with Cancer Using Multimodal Data 

   de Hond A.; van Buchem M.; Fanconi C.; et al. (2023)

   Studies in Health Technology and Informatics

   When patients with cancer develop depression, it is often left untreated. We developed a prediction model for depression risk within the first month after starting cancer treatment using machine learning and Natural Language Processing (NLP) models. The LASSO logistic regression model based on structured data performed well, whereas the NLP model based on only clinician notes did poorly. After further validation, prediction models for ...

   Journal Article

5. Progress in Diamond Detector Development 

   Wallny R.; Artuso M.; Bäni L.; et al. (2023)

   PoS: Proceedings of Science

   Detectors based on Chemical Vapor Deposition (CVD) diamond have been used successfully in Luminosity and Beam Condition Monitors (BCM) in the highest radiation areas of the LHC. Future experiments at CERN will accumulate an order of magnitude larger fluence. As a result, an enormous effort is underway to identify detector materials that can operate under fluences of 1 · 1016 n cm−2 and 1 · 1017 n cm−2. Diamond is one candidate due to its ...

   Conference Paper

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