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1. Research Directions in Decision Diagram Technology

   https://doi.org/10.1109/JVA60410.2023.00018  

   Ciardo, Gianfranco; Miner, Andrew S. (July 2023, IEEE)

   Binary decision diagrams (BDDs) have been a huge success story in hardware and software verification and are increasingly applied to a wide range of combinatorial problems. While BDDs can encode boolean-valued functions of boolean-valued variables, many BDD variants have been proposed, not just to improve their efficiency, but to manage multivalued domains (a straightforward extension), multivalued ranges (using several competitive alternatives), and two-dimensional data (relations and matrices instead of sets or vectors). Orthogonally to these extensions, much effort has been spent on variable order heuristics, an essential aspect that can affect memory and time requirements by up to an exponential factor. We survey some of these exciting results and discuss some fruitful research directions for further work. Index Terms—Binary decision diagrams, canonicity, discrete function encoding, variable order heuristics, Markov chains 

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2. Decadal-scale changes in the Georges Bank ecosystem: evidence from bulk and compound-specific stable isotope analyses of fish scales

   #Willis, Ciara; Llopiz, Joel; McMahon, Kelton W; Houghton, Leah; Hare Jon; McCarthy, Matthew D; Thorrold, Simon R (February 2024, Ocean Sciences Meeting)

   The impacts of climate change are increasingly apparent in the physical oceanographic environment of the global ocean, with cascading effects through individual species to entire food webs. Despite their importance, these ecosystem effects can be challenging to quantify and track. One angle from which to analyse ecosystem linkages is via compound-specific stable isotope analysis of carbon and nitrogen focused on individual amino acids. These analyses can provide individual-level information (e.g., dietary sources, trophic position) as well as ecosystem-level information (e.g., variability in biogeochemical cycling at the base of the food web, nutrient regimes, food web structure). In this study, we analyzed C and N stable isotopes in archived scales of haddock (Melanogrammus aeglefinus) collected over almost a century from Georges Bank (northeast US) to investigate changes in the diet and trophic status of the haddock population driven by climate change. Specifically, we used nitrogen isotopes to identify secular changes in the input of warm slope waters to the Gulf of Maine over the time series. In contrast, carbon isotopes in essential amino acids suggest that there have been relatively small changes in the source of carbon fueling haddock biomass over the past 100 years and nitrogen isotopes indicate negligible changes in haddock trophic position despite major oceanographic and climatic changes over this time period. Overall, we demonstrate the application of cutting edge molecular isotope tools to a historical archive to examine food web architecture over time in a changing oceanographic environment. 

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3. On the Estimation of Persistence Intensity Functions and Linear Representations of Persistence Diagrams

   Wu, Weichen; Kim, Jisu; Rinaldo, Alessandro (May 2024, Proceedings of The 27th International Conference on Artificial Intelligence and Statistics)

   Dasgupta, Sanjoy; Mandt, Stephan; Li, Yingzhen (Ed.)

   Persistence diagrams are one of the most pop- ular types of data summaries used in Topological Data Analysis. The prevailing statistical approach to analyzing persistence diagrams is concerned with filtering out topological noise. In this paper, we adopt a different viewpoint and aim at estimating the actual distribution of a random persistence diagram, which cap- tures both topological signal and noise. To that effect, Chazal and Divol (2019) proved that, under general conditions, the expected value of a random persistence diagram is a measure admitting a Lebesgue density, called the persistence intensity function. In this paper, we are concerned with estimating the persistence intensity function and a novel, normalized version of it – called the persistence density function. We present a class of kernel- based estimators based on an i.i.d. sample of persistence diagrams and derive estimation rates in the supremum norm. As a direct corollary, we obtain uniform consistency rates for estimating linear representations of persistence diagrams, including Betti numbers and persistence surfaces. Interestingly, the persistence density function delivers stronger statistical guarantees. 

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4. How I learned to stop worrying and love learned OS policies

   Saxena, Divyanshu; Chen, Jiayi; Yadalam, Sujay; Ro, Yeonju; Dwivedula, Rohit; Campbell, Eric; Akella, Aditya; Rossbach, Christopher J; Swift, Michael (May 2025, Workshop in Hot Topics in Operating Systems (HOTOS 25))

   While machine learning has been adopted across various fields, its ability to outperform traditional heuristics in operating systems is often met with justified skepticism. Concerns about unsafe decisions, opaque debugging processes, and the challenges of integrating ML into the kernel—given its stringent latency constraints and inherent complexity — make practitioners understandably cautious. This paper introduces Guardrails for the OS, a framework that allows kernel developers to declaratively specify system-level properties and define corrective actions to address property violations. The framework facilitates the compilation of these guardrails into monitors capable of running within the kernel. In this work, we establish the foundation for Guardrails, detailing its core abstractions, examining the problem space, and exploring potential solutions. 

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5. Evaluating the effectiveness of real-time closures for reducing susceptibility of small fish to capture

   https://doi.org/10.1093/icesjms/fsx152  

   Woods, Pamela J.; Elvarsson, Bjarki Þór; Sigurdsson, Thorsteinn; Stefánsson, Gunnar (August 2017, ICES Journal of Marine Science)

   Real-time spatial management in fisheries, a type of dynamic ocean management, uses nearly real-time data collection and dissemination to reduce susceptibility of certain species or age classes to being caught in mixed fisheries. However, as with many fisheries regulations, it is difficult to assess whether such a regulation can produce tangible results on population dynamics. In this study, we take advantage of a rare opportunity in which data regarding real-time closures (RTCs) are available for 1990–2014 alongside annual estimates of fishing mortality for three species (Atlantic cod, haddock, and herring) and catch for four species (all plus saithe) in Icelandic fisheries management. We use time series analyses to assess whether RTCs work as expected and yield a lower susceptibility of small fish to being caught, indicated by lower catch levels and selectivities (as estimated from fishing mortalities) in years with more closures. Results indicate that haddock and herring followed this pattern, but only under conditions of generally high fishing mortality. This study represents the first time evidence has been presented that real-time fishery closures can have a beneficial effect on population dynamics, but also suggests that results differ among species. 

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