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1. How range residency and long-range perception change encounter rates

   https://doi.org/10.1016/j.jtbi.2020.110267  

   Martinez-Garcia, Ricardo; Fleming, Christen H.; Seppelt, Ralf; Fagan, William F.; Calabrese, Justin M. (August 2020, Journal of Theoretical Biology)
2. Long Range Graph Benchmark

   Dwivedi, Vijay Prakash; Rampasek, Ladislav; Galkin, Michael; Parviz, Ali; Wolf, Guy; Luu, Anh Tuan; Beaini, Dominique (December 2022, NeurIPS)

   Graph Neural Networks (GNNs) that are based on the message passing (MP) paradigm generally exchange information between 1-hop neighbors to build node representations at each layer. In principle, such networks are not able to capture long-range interactions (LRI) that may be desired or necessary for learning a given task on graphs. Recently, there has been an increasing interest in development of Transformer-based methods for graphs that can consider full node connectivity beyond the original sparse structure, thus enabling the modeling of LRI. However, MP-GNNs that simply rely on 1-hop message passing often fare better in several existing graph benchmarks when combined with positional feature representations, among other innovations, hence limiting the perceived utility and ranking of Transformer-like architectures. Here, we present the Long Range Graph Benchmark (LRGB)1 with 5 graph learning datasets: PascalVOC-SP, COCO-SP, PCQM-Contact, Peptides-func and Peptides-struct that arguably require LRI reasoning to achieve strong performance in a given task. We benchmark both baseline GNNs and Graph Transformer networks to verify that the models which capture long-range dependencies perform significantly better on these tasks. Therefore, these datasets are suitable for benchmarking and exploration of MP-GNNs and Graph Transformer architectures that are intended to capture LRI. 

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3. Ultralong-range Rydberg molecules

   https://doi.org/10.1088/1361-6455/ad7459  

   Dunning, F_B; Kanungo, S_K; Yoshida, S. (October 2024, Journal of Physics B: Atomic, Molecular and Optical Physics)

   Abstract Ultralong-range Rydberg molecules (ULRMs) comprise a Rydberg atom in whose electron cloud are embedded one (or more) ground-state atoms that are weakly-bound through their scattering of the Rydberg electron. The existence of such novel molecular species was first predicted theoretically in 2000 but they were not observed in the laboratory until 2009. Since that time, interest in their chemical properties, physical characteristics, and applications has increased dramatically. We discuss here recent advances in the study of ULRMs. These have yielded a wealth of information regarding low-energy electron scattering in an energy regime difficult to access using alternate techniques, and have provided a valuable probe of non-local spatial correlations in quantum gases elucidating the effects of quantum statistics. Studies in dense environments, where the Rydberg electron cloud can enclose hundreds, or even thousands, of ground-state atoms, have revealed many-body effects such as the creation of Rydberg polarons. The production of overlapping clouds of different cold atoms has enabled the creation of heteronuclear ULRMs. Indeed, the wide variety of atomic and molecular species that can now be cooled promises, through the careful choice of atomic (or molecular) species, to enable the production of ULRMs with properties tailored to meet a variety of different needs and applications. 

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4. Orthogonal Range Searching in Moderate Dimensions: k-d Trees and Range Trees Strike Back

   https://doi.org/10.1007/s00454-019-00062-5  

   Chan, Timothy M. (June 2019, Discrete & Computational Geometry)
5. Sediment selection: range-expanding fiddler crabs are better burrowers than their historic-range counterparts

   https://doi.org/10.3354/meps13811  

   Wong, RJ; Roy, MS; Byrnes, JEK (September 2021, Marine Ecology Progress Series)

   Climate change plays a large role in driving species range shifts; however, the physical characteristics of an environment can also influence and alter species distributions. In New England salt marshes, the mud fiddler crab Minuca pugnax is expanding its range north of Cape Cod, MA, into the Gulf of Maine (GoM) due to warming waters. The burrowing lifestyle of M. pugnax means sediment compaction in salt marshes may influence the ability of crabs to dig, with more compact soils being resistant to burrowing. Previous studies indicate that salt marshes along the GoM have a higher sediment compaction relative to marshes south of Cape Cod. Physical characteristics of this habitat may be influencing the burrowing performance of M. pugnax and therefore the continuation of their northward range expansion into the GoM. We conducted a controlled laboratory experiment to determine if compaction affects the burrowing activity of M. pugnax in historical and range-expanded populations. We manipulated sediment compaction in standardized lab assays and measured crab burrowing performance with individuals collected from Nantucket (NAN, i.e. historical range) and the Plum Island Estuary (PIE, i.e. expanded range). We determined compaction negatively affected burrowing ability in crabs from both sites; however, crabs from PIE have a higher probability of burrowing in higher sediment compactions than NAN crabs. In addition, PIE crabs were more likely to burrow overall. We conclude that site level differences in compaction are likely altering burrowing behavior in the crab’s expanded-range territory by way of local adaptation or phenotypic plasticity. 

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