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1. Physical and stoichiometric controls on stream respiration in a headwater stream

   https://doi.org/10.5194/bg-20-3353-2023  

   Dorley, Jancoba; Singley, Joel; Covino, Tim; Singha, Kamini; Gooseff, Michael; Van Horn, David; González-Pinzón, Ricardo (January 2023, Biogeosciences)

   Abstract. Many studies in ecohydrology focusing on hydrologictransport argue that longer residence times across a stream ecosystem shouldconsistently result in higher biological uptake of carbon, nutrients, andoxygen. This consideration does not incorporate the potential forbiologically mediated reactions to be limited by stoichiometric imbalances.Based on the relevance and co-dependences between hydrologic exchange,stoichiometry, and biological uptake and acknowledging the limited amountof field studies available to determine their net effects on the retentionand export of resources, we quantified how microbial respiration iscontrolled by the interactions between and the supply of essential nutrients (C, N, and P)in a headwater stream in Colorado, USA. For this, we conducted two rounds ofnutrient experiments, each consisting of four sets of continuous injectionsof Cl− as a conservative tracer, resazurin as a proxy for aerobicrespiration, and one of the following nutrient treatments: (a) N, (b) N+C,(c) N+P, or (d) C+N+P. Nutrient treatments were considered to be knownsystem modifications that alter metabolism, and statistical tests helpedidentify the relationships between reach-scale hydrologic transport andrespiration metrics. We found that as discharge changed significantlybetween rounds and across stoichiometric treatments, (a) transient storagemainly occurred in pools lateral to the main channel and was proportional todischarge, and (b) microbial respiration remained similar between rounds andacross stoichiometric treatments. Our results contradict the notion thathydrologic transport alone is a dominant control on biogeochemicalprocessing and suggest that complex interactions between hydrology, resourcesupply, and biological community function are responsible for drivingin-stream respiration. 

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2. Destabilization of a planar liquid stream by a co-flowing turbulent gas stream

   https://doi.org/10.1016/j.ijmultiphaseflow.2019.103121  

   Jiang, Delin; Ling, Yue (September 2019, International Journal of Multiphase Flow)
3. Tidal disruption discs formed and fed by stream–stream and stream–disc interactions in global GRHD simulations

   https://doi.org/10.1093/mnras/stab3444  

   Andalman, Zachary L.; Liska, Matthew T. P.; Tchekhovskoy, Alexander; Coughlin, Eric R.; Stone, Nicholas (November 2021, Monthly Notices of the Royal Astronomical Society)

   ABSTRACT When a star passes close to a supermassive black hole (BH), the BH’s tidal forces rip it apart into a thin stream, leading to a tidal disruption event (TDE). In this work, we study the post-disruption phase of TDEs in general relativistic hydrodynamics (GRHD) using our GPU-accelerated code h-amr. We carry out the first grid-based simulation of a deep-penetration TDE (β = 7) with realistic system parameters: a black hole-to-star mass ratio of 106, a parabolic stellar trajectory, and a non-zero BH spin. We also carry out a simulation of a tilted TDE whose stellar orbit is inclined relative to the BH midplane. We show that for our aligned TDE, an accretion disc forms due to the dissipation of orbital energy with ∼20 per cent of the infalling material reaching the BH. The dissipation is initially dominated by violent self-intersections and later by stream–disc interactions near the pericentre. The self-intersections completely disrupt the incoming stream, resulting in five distinct self-intersection events separated by approximately 12 h and a flaring in the accretion rate. We also find that the disc is eccentric with mean eccentricity e ≈ 0.88. For our tilted TDE, we find only partial self-intersections due to nodal precession near pericentre. Although these partial intersections eject gas out of the orbital plane, an accretion disc still forms with a similar accreted fraction of the material to the aligned case. These results have important implications for disc formation in realistic tidal disruptions. For instance, the periodicity in accretion rate induced by the complete stream disruption may explain the flaring events from Swift J1644+57. 

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4. When does a stream become a river?

   https://doi.org/10.1002/rra.4185  

   Czuba, Jonathan_A; Allen, George_H (July 2023, River Research and Applications)

   Abstract The distinction between a “stream” and “river” is imprecise and vague despite the popular usage of the terms across disciplines for describing flowing waterbodies. Based on an analysis of named flowing waterbodies in the continental United States, we suggest a bank‐to‐bank channel width of 15 m as a working threshold in defining smaller “streams” from larger “rivers.” 

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5. DART: A Scalable and Adaptive Edge Stream Processing Engine

   Liu, Pinchao; Da Silva, Dilma; Hu, Liting (July 2021, USENIX Annual Technical Conference)

   null (Ed.)

   Many Internet of Things (IoT) applications are time-critical and dynamically changing. However, traditional data processing systems (e.g., stream processing systems, cloud-based IoT data processing systems, wide-area data analytics systems) are not well-suited for these IoT applications. These systems often do not scale well with a large number of concurrently running IoT applications, do not support low-latency processing under limited computing resources, and do not adapt to the level of heterogeneity and dynamicity commonly present at edge environments. This suggests a need for a new edge stream processing system that advances the stream processing paradigm to achieve efficiency and flexibility under the constraints presented by edge computing architectures. We present \textsc{Dart}, a scalable and adaptive edge stream processing engine that enables fast processing of a large number of concurrent running IoT applications’ queries in dynamic edge environments. The novelty of our work is the introduction of a dynamic dataflow abstraction by leveraging distributed hash table (DHT) based peer-to-peer (P2P) overlay networks, which can automatically place, chain, and scale stream operators to reduce query latency, adapt to edge dynamics, and recover from failures. We show analytically and empirically that DART outperforms Storm and EdgeWise on query latency and significantly improves scalability and adaptability when processing a large number of real-world IoT stream applications' queries. DART significantly reduces application deployment setup times, becoming the first streaming engine to support DevOps for IoT applications on edge platforms. 

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