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1. Genome of a novel Sediminibacterium discovered in association with two species of freshwater cyanobacteria from streams in Southern California

   https://doi.org/10.1093/g3journal/jkac123  

   Sethuraman, Arun; Stancheva, Rosalina; Sanders, Ciara; Caceres, Lakme; Castro, David; Hausknecht-Buss, Hannah; Henry, Simone; Johansen, Haven; Kasler, Antolette; Lastor, Sandy; et al (May 2022, G3 Genes|Genomes|Genetics)

   Abstract Here, we report the discovery of a novel Sediminibacterium sequenced from laboratory cultures of freshwater stream cyanobacteria from sites in Southern California, grown in BG11 medium. Our genome-wide analyses reveal a highly contiguous and complete genome (97% BUSCO) that is placed within sediminibacterial clades in phylogenomic analyses. Functional annotation indicates the presence of genes that could be involved in mutualistic/commensal relationship with associated cyanobacterial hosts. 

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2. Active quickest detection when monitoring multi-streams with two affected streams

   Xu, Qunzhi; Mei, Yajun (January 2022, Proceeding of 2022 IEEE International Symposium on Information Theory (ISIT))
3. Maximum Matching in Two, Three, and a Few More Passes Over Graph Streams

   https://doi.org/10.4230/LIPIcs.APPROX-RANDOM.2017.15  

   Kale, Sagar; Tirodkar, Sumedh (August 2017, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques)

   We consider the maximum matching problem in the semi-streaming model formalized by Feigenbaum, Kannan, McGregor, Suri, and Zhang that is inspired by giant graphs of today. As our main result, we give a two-pass (1/2 + 1/16)-approximation algorithm for triangle-free graphs and a two-pass (1/2 + 1/32)-approximation algorithm for general graphs; these improve the approximation ratios of 1/2 + 1/52 for bipartite graphs and 1/2 + 1/140 for general graphs by Konrad, Magniez, and Mathieu. In three passes, we are able to achieve approximation ratios of 1/2 + 1/10 for triangle-free graphs and 1/2 + 1/19.753 for general graphs. We also give a multi-pass algorithm where we bound the number of passes precisely—we give a (2/3 − ε)- approximation algorithm that uses 2/(3ε) passes for triangle-free graphs and 4/(3ε) passes for general graphs. Our algorithms are simple and combinatorial, use O(n log n) space, and (can be implemented to) have O(1) update time per edge. For general graphs, our multi-pass algorithm improves the best known deterministic algorithms in terms of the number of passes: * Ahn and Guha give a (2/3−ε)-approximation algorithm that uses O(log(1/ε)/ε2) passes, whereas our (2/3 − ε)-approximation algorithm uses 4/(3ε) passes; * they also give a (1 − ε)-approximation algorithm that uses O(log n · poly(1/ε)) passes, where n is the number of vertices of the input graph; although our algorithm is (2/3−ε)-approximation, our number of passes do not depend on n. Earlier multi-pass algorithms either have a large constant inside big-O notation for the number of passes or the constant cannot be determined due to the involved analysis, so our multi-pass algorithm should use much fewer passes for approximation ratios bounded slightly below 2/3. 

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4. AGE-SPECIFIC PATTERNS OF OCCURRENCE, DENSITY, AND GROWTH OF TWO CYPRINID FISHES IN HEADWATER PRAIRIE STREAMS

   https://doi.org/10.1894/0038-4909-65.3-4.205  

   Hedden, Skyler C.; Gido, Keith B. (September 2020, The Southwestern Naturalist)
5. Disentangling In‐Stream Nitrate Uptake Pathways Based on Two‐Station High‐Frequency Monitoring in High‐Order Streams

   https://doi.org/10.1029/2022WR032329  

   Zhang, Xiaolin; Yang, Xiaoqiang; Hensley, Robert; Lorke, Andreas; Rode, Michael (March 2023, Water Resources Research)