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Collateral sensitivity, where resistance to one drug confers heightened sensitivity to another, offers a promising strategy for combating antimicrobial resistance, yet predicting resultant evolutionary dynamics remains a significant challenge. We propose here a mathematical model that integrates fitness trade-offs and adaptive landscapes to predict the evolution of collateral sensitivity pathways, providing insights into optimizing sequential drug therapies. Our approach embeds collateral information into a network of switched systems, allowing us to abstract the effects of sequential antibiotic exposure on antimicrobial resistance. We analyze the system stability at disease-free equilibrium and employ set-control theory to tailor therapeutic windows. Consequently, we propose a computational algorithm to identify effective sequential therapies to counter antibiotic resistance. By leveraging our theory with data on collateral sensivity interactions, we predict scenarios that may prevent bacterial escape for chronic Pseudomonas aeruginosa infections. 

Abstract Predictive Maintenance (PdM) emerges as a critical task of Industry 4.0, driving operational efficiency, minimizing downtime, and reducing maintenance costs. However, real-world industrial environments present unsolved challenges, especially in predicting simultaneous and correlated faults under evolving conditions. Traditional batch-based and deep learning approaches for simultaneous fault prediction often fall short due to their assumptions of static data distributions and high computational demands, making them unsuitable for dynamic, resource-constrained systems. In response, we propose OEMLHAT (Online Ensemble of Multi-Label Hoeffding Adaptive Trees), a novel model tailored for real-time, multi-label fault prediction in non-stationary industrial settings. OEMLHAT introduces a scalable online ensemble architecture that integrates online bagging, dynamic feature subspacing, and adaptive output weighting. This design allows it to efficiently handle concept drift, high-dimensional input spaces, and label sparsity, key bottlenecks in existing PdM solutions. Experimental results on three public multi-label PdM case studies demonstrate substantial improvements in predictive performance of OEMLHAT over previous batch-based and online proposals for multi-label classification, particularly with an average improvement in micro-averaged F1-score of 18.49% over the second most-accurate batch-based proposal and of 8.56% in the case of the second best online model. By addressing a critical gap in online multi-label learning for PdM, this work provides a robust and interpretable solution for next-generation industrial monitoring systems for fault detection, particularly for rare and concurrent failures. 

The causes underlying Holocene glacier fluctuations remain elusive, despite decades of research efforts. Cosmogenic nuclide dating has allowed systematic study and thus improved knowledge of glacier-climate dynamics during this time frame, in part by filling in geographical gaps in both hemispheres. Here we present a new comprehensive Holocene moraine chronology from Mt. San Lorenzo (47°S) in central Patagonia, Southern Hemisphere. Twenty-four new 10 Be ages, together with three published ages, indicate that the Río Tranquilo glacier approached its Holocene maximum position sometime, or possibly on multiple occasions, between 9,860 ± 180 and 6,730 ± 130 years. This event(s) was followed by a sequence of slightly smaller advances at 5,750 ± 220, 4,290 ± 100 (?), 3,490 ± 140, 1,440 ± 60, between 670 ± 20 and 430 ± 20, and at 390 ± 10 years ago. The Tranquilo record documents centennial to millennial-scale glacier advances throughout the Holocene, and is consistent with recent glacier chronologies from central and southern Patagonia. This pattern correlates well with that of multiple moraine-building events with slightly decreasing net extent, as is observed at other sites in the Southern Hemisphere (i.e., Patagonia, New Zealand and Antarctic Peninsula) throughout the early, middle and late Holocene. This is in stark contrast to the typical Holocene mountain glacier pattern in the Northern Hemisphere, as documented in the European Alps, Scandinavia and Canada, where small glaciers in the early-to-mid Holocene gave way to more-extensive glacier advances during the late Holocene, culminating in the Little Ice Age expansion. We posit that this past asymmetry between the Southern and Northern hemisphere glacier patterns is due to natural forcing that has been recently overwhelmed by anthropogenic greenhouse gas driven warming, which is causing interhemispherically synchronized glacier retreat unprecedented during the Holocene. 

Abstract In the Cordillera Darwin, southernmost South America, we used 10 Be and 14 C dating, dendrochronology, and historical observations to reconstruct the glacial history of the Dalla Vedova valley from deglacial time to the present. After deglacial recession into northeastern Darwin and Dalla Vedova, by ~16 ka, evidence indicates a glacial advance at ~13 ka coeval with the Antarctic Cold Reversal. The next robustly dated glacial expansion occurred at 870 ± 60 calendar yr ago (approximately AD 1150), followed by less-extensive dendrochronologically constrained advances from shortly before AD 1836 to the mid-twentieth century. Our record is consistent with most studies within the Cordillera Darwin that show that the Holocene glacial maximum occurred during the last millennium. This pattern contrasts with the extensive early- and mid-Holocene glacier expansions farther north in Patagonia; furthermore, an advance at 870 ± 60 yr ago may suggest out-of-phase glacial advances occurred within the Cordillera Darwin relative to Patagonia. We speculate that a southward shift of westerlies and associated climate regimes toward the southernmost tip of the continent, about 900–800 yr ago, provides a mechanism by which some glaciers advanced in the Cordillera Darwin during what is generally considered a warm and dry period to the north in Patagonia.