Streaming System Research Articles

New sensitive tools to characterize meta-metabolome response to short- and long-term cobalt exposure in dynamic river biofilm communities

Untargeted metabolomics is a non-a priori analysis of biomolecules that characterizes the metabolome variations induced by short- and long-term exposures to stressors. Even if the metabolite annotation remains lacunar due to database gaps, the global metabolomic fingerprint allows for trend analyses of dose-response curves for hundreds of cellular metabolites. Analysis of dose/time-response curve trends (biphasic or monotonic) of untargeted metabolomic features would thus allow the use of all the chemical signals obtained in order to determine stress levels (defense or damage) in organisms. To develop this approach in a context of time-dependent microbial community changes, mature river biofilms were exposed for 1 month to four cobalt (Co) concentrations (from background concentration to 1 × 10−6 M) in an open system of artificial streams. The meta-metabolomic response of biofilms was compared against a multitude of biological parameters (including bioaccumulation, biomass, chlorophyll a content, composition and structure of prokaryotic and eukaryotic communities) monitored at set exposure times (from 1 h to 28 d). Cobalt exposure induced extremely rapid responses of the meta-metabolome, with time range inducing defense responses (TRIDeR) of around 10 s, and time range inducing damage responses (TRIDaR) of several hours. Even in biofilms whose structure had been altered by Co bioaccumulation (reduced biomass, chlorophyll a contents and changes in the composition and diversity of prokaryotic and eukaryotic communities), concentration range inducing defense responses (CRIDeR) with similar initiation thresholds (1.41 ± 0.77 × 10−10 M Co2+ added in the exposure medium) were set up at the meta-metabolome level at every time point. In contrast, the concentration range inducing damage responses (CRIDaR) initiation thresholds increased by 10 times in long-term Co exposed biofilms. The present study demonstrates that defense and damage responses of biofilm meta-metabolome exposed to Co are rapidly and sustainably impacted, even within tolerant and resistant microbial communities.

An automated ICU agitation monitoring system for video streaming using deep learning classification.

To address the challenge of assessing sedation status in critically ill patients in the intensive care unit (ICU), we aimed to develop a non-contact automatic classifier of agitation using artificial intelligence and deep learning. We collected the video recordings of ICU patients and cut them into 30-second (30-s) and 2-second (2-s) segments. All of the segments were annotated with the status of agitation as "Attention" and "Non-attention". After transforming the video segments into movement quantification, we constructed the models of agitation classifiers with Threshold, Random Forest, and LSTM and evaluated their performances. The video recording segmentation yielded 427 30-s and 6405 2-s segments from 61 patients for model construction. The LSTM model achieved remarkable accuracy (ACC 0.92, AUC 0.91), outperforming other methods. Our study proposes an advanced monitoring system combining LSTM and image processing to ensure mild patient sedation in ICU care. LSTM proves to be the optimal choice for accurate monitoring. Future efforts should prioritize expanding data collection and enhancing system integration for practical application.

Influence of Riparian Conditions on Physical Instream Habitats in Trout Streams in Southeastern Minnesota, USA

Rivers across the globe experience and respond to changes within the riparian corridor. Disturbance of the riparian corridor can affect warmwater, intermediate, and coldwater streams, which can negatively influence instream physical structure and biological communities. This study focused on assessing the influence of the riparian habitat on instream structure within the Whitewater River, a coldwater stream system within an agricultural watershed in southeastern Minnesota, USA. To understand the influence of the riparian zone on the physical instream habitat, twenty variables (riparian, n = 9; instream, n = 11) were measured at 57 sites across three forks of the Whitewater using a transect method every 10 m across a 150 m reach. We used a modified Wentworth scale approach to assess coarse and fine substrates to describe habitat conditions. Canonical correlation detected significant associations between riparian and instream variables across the river forks, and indicated that wider riparian buffers, more bank grass and shrubs, longer overhanging vegetation, limited bare soil, and more rocks on banks were significantly associated with increased instream cover, high levels of coarse substrates with reduced embeddedness, increased pool habitats, and reduced fine sediments. In contrast, excessive fine sediments, lack of riffle habitat, reduced coarse substrates, and high width to depth ratios indicative of an impaired instream habitat were associated with narrow riparian buffers and high percentages of bare soil on banks. Riparian corridors have the capacity to enhance and protect physical instream habitats and overall ecosystem health when managed properly. Wide, grassy riparian corridors with stable banks, overhanging vegetation, and limited shade from trees should protect and/or enhance the instream physical habitat, providing the structural diversity favored by aquatic communities. We recommend revising the current Best Management Practices to include monitoring for impairments in the riparia, while promoting and developing good land stewardship with private landowners which can be effective in improving river ecosystems in agricultural settings.

Reconnecting a stream channel to its floodplain: implications for benthic diatoms and macroinvertebrate trophic structure

Streams systems draining upland landscapes provide valuable ecosystem services, but they are vulnerable to incision and channelization caused by anthropogenic disturbance. Restoring a degraded stream to its pre‐disturbance condition by reconnecting the channel to its historical floodplain aims to recover lost hydro‐morphological processes and functions. Seeking evidence to indicate whether that aim is met in practice, we examined diatoms and the stream macroinvertebrate trophic structures in three reaches of Whychus Creek, Oregon, United States. Two reaches were reconnected to their pre‐disturbance floodplains in 2012 and 2016. The third, control reach, was not restored and was selected to represent the degraded stream condition prior to restoration. Ordinations showed that benthic diatom species composition shifted from the control reach to the restored reaches. Compared to the control reach, reconnection decreased the percentages of diatoms with nitrogen (N)‐fixing cyanobacterial endosymbionts in the 2012 restored reach and decreased diatoms tolerant to low N conditions in both the restored reaches. δ15N values in both stream macroinvertebrates and tree leaves in the riparian zone were higher in the restored reaches. These findings suggest that floodplain reconnection may modify hydro‐morphological processes and ecosystem functions in ways that enhance organic matter retention and hyporheic exchange, resulting in increased nutrient availability, improved nutrient cycling, and greater primary productivity. More generally, our results suggest that characterizing diatom species composition and trophic interactions using stable isotopes provides the basis for identifying and evaluating the beneficial effects of stream restoration on ecosystem functions and the food‐web.

MetaABR: A Meta-Learning Approach on Adaptative Bitrate Selection for Video Streaming

Video streaming is one of the most popular Internet applications that makes up a large amount of Internet traffic. A fundamental mechanism in video streaming is adaptive bitrate (ABR) selection which decides the proper compression level for each chunk of a video to optimize the users' quality of experience (QoE). The existing ABR algorithms require significant tuning and do not generalize to diverse network conditions and personalized QoE objectives. In this paper, we propose a novel framework for meta-learning based ABR design and discuss challenges of deploying learning based ABR mechanism in real-world video streaming systems. We utilize the proposed framework to design MetaABR, a novel adaptive bitrate selection algorithm based on meta-reinforcement learning to maximize users' QoE. By jointly training multiple learning tasks with a shared meta-critic, it can provide transferrable meta-knowledge to supervise bitrate selection across tasks, and can be applied to efficiently learn a new task in unseen environment with only a few trials. We implement MetaABR on an emulation platform which connects to the Linux network protocol stack through virtual network interfaces. Extensive experiments based on real-world traces and wireless testbed show that MetaABR achieves the best comprehensive QoE compared with the state-of-the-art ABR algorithms in a variety of network environments.

Climate-driven differences in flow regimes alter tropical freshwater ecosystems with consequences for an endemic shrimp

Climate-driven shifts in the natural flow regime can threaten species persistence in stream systems, and anticipating such shifts before they occur is critical for conservation. We can explore how climate change may impact biota by examining natural systems that differ in terms of climate yet are similar in terms of other landscape features such as geology, size, and elevation. Across an established precipitation and hydrologic gradient on the east coast of Hawaii Island, we sampled stream habitat and populations of the endemic migratory mountain shrimp Atyoida bisulcata over three years and examined how habitat as well as population metrics and individual condition respond to differences in stream flow. Along the precipitation gradient, baseflow declined and streams shifted from run/riffle systems with moss cover to those with predominately pools and limited available habitat. Across years, baseflow conditions were relatively consistent within streams while measures of stream flow stability and the duration of high flows were more variable. Streams with high and persistent baseflow had greater atyid biomass density with larger individuals less prone to disease. Within-stream interannual variation in baseflow was low relative to differences across streams, and most A. bisulcata metrics also had low within-stream interannual variability, making average baseflow an appropriate surrogate for differences in suitability. However, extremes in annual rainfall may result in high variability in A. bisulcata metrics within a single stream due to seasonal drying or persistent high flows, highlighting the importance of long-term monitoring to fully understand population responses to climate-mediated stream flow. Our study suggests that changes in rainfall patterns will alter stream flow and may ultimately negatively influence tropical stream organisms.

Improved capabilities of global ocean reanalyses for analysing sea level variability near the Atlantic and Gulf of Mexico Coastal U.S.

Realistic representation of monthly sea level anomalies in coastal regions has been a challenge for global ocean reanalyses. This is especially the case in coastal regions where sea levels are influenced by western boundary currents such as near the U.S. Atlantic Coast and the Gulf of Mexico. For these regions, most ocean reanalyses compare poorly to observations. Problems in reanalyses include errors in data assimilation and horizontal resolutions that are too coarse to simulate energetic currents like the Gulf Stream and Loop Current System. However, model capabilities are advancing with improved data assimilation and higher resolution. Here, we show that some current-generation ocean reanalyses produce monthly sea level anomalies with improved skill when compared to satellite altimetry observations of sea surface heights. Using tide gauge observations for coastal verification, we find the highest skill associated with the GLORYS12 and HYCOM ocean reanalyses. Both systems assimilate altimetry observations and have eddy-resolving horizontal resolutions (1/12°). We found less skill in three other ocean reanalyses (ACCESS-S2, ORAS5, and ORAP6) with coarser, though still eddy-permitting, resolutions (1/4°). The operational reanalysis from ECMWF (ORAS5) and their pilot reanalysis (ORAP6) provide an interesting comparison because the latter assimilates altimetry globally and with more weight, as well as assimilating ocean observations over continental shelves. We find these attributes associated with improved skill near many tide gauges. We also assessed an older reanalysis (CFSR), which has the lowest skill likely due to its lower resolution (1/2°) and lack of altimetry assimilation. ACCESS-S2 likewise does not assimilate altimetry, although its skill is much better than CFSR and only somewhat lower than ORAS5. Since coastal flooding is influenced by sea level anomalies, the recent development of skilful ocean reanalyses on monthly timescales may be useful for better understanding the physical processes associated with flood risks.

Revisiting the multidecadal variability of North Atlantic Ocean circulation and climate

The World Ocean’s surface, particularly in the North Atlantic, has been heating up for decades. There was concern that the thermohaline circulation and essential climate variables, such as the temperature and salinity of seawater, could undergo substantial changes in response to this surface warming. The Atlantic Meridional Overturning Circulation (AMOC) has changed noticeably over the last centennial and possibly slowed down in recent decades. Therefore, concerns about the future of the North Atlantic Ocean climate are warranted. The key to understanding the North Atlantic current climate trajectory is to identify how the decadal climate responds to ongoing surface warming. This issue is addressed using in-situ data from the World Ocean Atlas covering 1955-1964 to 2005-2017 and from the SODA reanalysis project for the most recent decades of 1980-2019 as fingerprints of the North Atlantic three-dimensional circulation and AMOC’s dynamics. It is shown that although the entire North Atlantic is systematically warming, the climate trajectories in different sub-regions of the North Atlantic reveal radically different characteristics of regional decadal variability. There is also a slowdown of the thermohaline geostrophic circulation everywhere in the North Atlantic during the most recent decade. The warming trends in the subpolar North Atlantic lag behind the subtropical gyre and Nordic Seas warming by at least a decade. The climate and circulation in the North Atlantic remained robust from 1955-1994, with the last two decades (1995-2017) marked by a noticeable reduction in AMOC strength, which may be closely linked to changes in the geometry and strength of the Gulf Stream system.

The bay barnacle Amphibalanus improvisus (Darwin, 1854) in the Pleistocene of Europe? A review of Pleistocene Balanidae of northern Central Europe

ABSTRACTThe bay barnacle Amphibalanus improvisus (Darwin, 1854) has been found in Northern Germany in brackish marine sediments of the Holsteinian interglacial. Whereas the cause of the contemporary distribution of this species is anthropogenic and there is evidence that it has resulted mainly from shipping, the fossil findings demonstrate that A. improvisus had also already reached Europe naturally during the Pleistocene in Europe, probably via the Gulf Stream system of the Atlantic. Today, A. improvisus is considered one of the most successful aquatic invasive species worldwide and it is characterized by a high environmental tolerance. The ingression of the Holsteinian Sea, during the Pleistocene, took place during the climate optimum from the North Sea into the ‘Elbe Estuary’ through the Hamburg region and far to the south‐east into Brandenburg. It has been possible to reconstruct the palaeo‐ecological conditions based in particular on molluscs. Accordingly, environmental conditions ranged from normal marine in the north, via brackish in the transitional area to limnic–fluviatile in the Berlin region. The morphological features of the bay barnacles and their ecological parameters are described here in detail. In addition, we provide a general review of the known Pleistocene Balanidae in northern central Europe.

Seasonal prediction of end-of-dry-season watershed behavior in a highly interconnected alluvial watershed in northern California

Abstract. In undammed watersheds in Mediterranean climates, the timing and abruptness of the transition from the dry season to the wet season have major implications for aquatic ecosystems. Of particular concern in many coastal areas is whether this transition can provide sufficient flows at the right time to allow passage for spawning anadromous fish, which is determined by dry season baseflow rates and the timing of the onset of the rainy season. In (semi-) ephemeral watershed systems, these functional flows also dictate the timing of full reconnection of the stream system. In this study, we propose methods to predict, approximately 5 months in advance, two key hydrologic metrics in the undammed rural Scott River watershed in northern California. The two metrics are intended to characterize (1) the severity of a dry year and (2) the relative timing of the transition from the dry to the wet season. The ability to predict these metrics in advance could support seasonal adaptive management. The first metric is the minimum 30 d dry season baseflow volume, Vmin, which occurs at the end of the dry season (September–October) in this Mediterranean climate. The second metric is the cumulative precipitation, starting 1 September, necessary to bring the watershed to a “full” or “spilling” condition (i.e., initiate the onset of wet season storm- or baseflows) after the end of the dry season, referred to here as Pspill. As potential predictors of these two metrics, we assess maximum snowpack, cumulative precipitation, the timing of the snowpack and precipitation, spring groundwater levels, spring river flows, reference evapotranspiration, and a subset of these metrics from the previous water year. Though many of these predictors are correlated with the two metrics of interest, we find that the best prediction for both metrics is a linear combination of the maximum snowpack water content and total October–April precipitation. These two linear models could reproduce historical values of Vmin and Pspill with an average model error (RMSE) of 1.4 Mm3 per 30 d (19.4 cfs) and 25.4 mm (1 in.), corresponding to 49 % and 37 % of mean observed values, respectively. Although these predictive indices could be used by governance entities to support local water management, careful consideration of baseline conditions used as a basis for prediction is necessary.

TrafAda: Cost-Aware Traffic Adaptation for Maximizing Bitrates in Live Streaming

The business growth of live streaming causes expensive bandwidth costs from the Content Delivery Network service. It necessitates traffic adaptation, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , adapting video bitrates for cost-efficient bandwidth utilization, especially under the 95 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>th</i> </sup> percentile pricing. However, our data-driven investigations indicate the existing methods are hard to achieve bitrate-cost balance in a long month-level billing cycle due to dynamic traffic patterns. We propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TrafAda</i> , a learning-based cost-aware traffic adaptation method consisting of i) an ultra-long-term bandwidth demand forecasting model to learn complex bandwidth usage patterns, and ii) an imitation learning-based bitrate decision mechanism to optimize the ultra-long-term objective. We have implemented and deployed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TrafAda</i> on a large-scale live streaming system in China serving over one billion viewers from 388 cities. The results show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TrafAda</i> improves peak-hour bitrate, quality of experience (QoE), and watching time by 34.75%, 44.56%, and 10.68%, respectively, without extra bandwidth cost, which can be converted to a considerable value for a commercial system.

Creating a systematic prioritization of stream reaches for conservation of aquatic species

AbstractHuman impacts on aquatic ecosystems have resulted in systemic declines of global freshwater species abundance and richness. Conservation and governmental groups worldwide have designated protected areas to preserve the remaining diversity. The biodiversity hotspot approach, which designates areas based on high levels of species richness, has been useful for identifying areas to protect both terrestrial and aquatic species. However, for freshwater species, additional approaches are warranted to identify specific stream reaches for protection and/or restoration. To address this issue, we present a methodology to create a Gridded River Identification System (GRIS) for river segments based on 30 arc‐second grids (~0.9 km) using the USGS National Hydrography High Resolution Dataset. To demonstrate the utility of this approach, we obtained occurrence data for six imperiled freshwater mussel species in Texas and created ensemble species distribution models (ESDMs) based on climate and topographical variables. Predicted occupancies were overlayed onto the GRIS in Texas. The predicted occupancies were rank ordered from 1 to 5, with 1 being the lowest probability of occupancy and 5 being the greatest. The rank‐ordered segments were then used to identify reaches for conservation and restoration activities. Our approach is novel and widely applicable to other freshwater species so long as distribution information is available. The GRIS can also be easily developed for stream systems outside of the current study area. Future studies could build upon our framework by incorporating additional taxa data and projected changes in climate and land use.

Deep Variational Learning for 360° Adaptive Streaming

Prediction of head movements in immersive media is key to designing efficient streaming systems able to focus the bandwidth budget on visible areas of the content. However, most of the numerous proposals made to predict user head motion in 360° images and videos do not explicitly consider a prominent characteristic of the head motion data: its intrinsic uncertainty. In this article, we present an approach to generate multiple plausible futures of head motion in 360° videos, given a common past trajectory. To our knowledge, this is the first work that considers the problem of multiple head motion prediction for 360° video streaming. We introduce our discrete variational multiple sequence (DVMS) learning framework, which builds on deep latent variable models. We design a training procedure to obtain a flexible, lightweight stochastic prediction model compatible with sequence-to-sequence neural architectures. Experimental results on 4 different datasets show that our method DVMS outperforms competitors adapted from the self-driving domain by up to 41% on prediction horizons up to 5 sec., at lower computational and memory costs. To understand how the learned features account for the motion uncertainty, we analyze the structure of the learned latent space and connect it with the physical properties of the trajectories. We also introduce a method to estimate the likelihood of each generated trajectory, enabling the integration of DVMS in a streaming system. We hence deploy an extensive evaluation of the interest of our DVMS proposal for a streaming system. To do so, we first introduce a new Python-based 360° streaming simulator that we make available to the community. On real-world user, video, and networking data, we show that predicting multiple trajectories yields higher fairness between the traces, the gains for 20 to 30% of the users reaching up to 10% in visual quality for the best number K of trajectories to generate.

Fuzzy logic as a novel approach to predict biological condition gradient of various streams in Ceyhan River Basin (Turkey)

Creating a method to categorize the ecological status of streams according to their biological conditions and establishing scientifically defensible nutrient criteria to protect their biotic integrity poses significant challenges. Biomonitoring of least disturbed areas is an important issue to accurately assess the ecological status of surface waters and ensure their sustainability. The fuzzy logic as a novel approach was firstly applied to evaluate the biological condition gradient of 44 sampled streams in the Ceyhan River Basin, utilizing two diatom indices, total phosphorus (TP), electrical conductivity (EC), and CORINE data. The fuzzy logic was employed to examine variations in the diatom compositions and land cover based on biological condition gradients (BCGs) of various streams and to assess the suitability of BCG in evaluating the health of studied stream systems. A three-layer fuzzy logic was constructed to predict BCGs of steams based on input data, with diatom metrics, TP, and EC representing BCGdia and land cover variables contributing to BCGland. The effects of operating variables were studied to optimize BCG results. The highest BCG score (0.85) was determined in Aksu Spring Brook in the spring, whereas the lowest value (0.05) was calculated in Erkenez Stream3 in the summer. BCGs showed strong relationships with nutrients, altitude, and EC. Results of BCGs indicated that sampling stations have various ecological statuses ranging from bad to high in the Ceyhan River Basin. The BCGdia and BCGland made important contributions to determine the ecological status of streams in the Ceyhan River Basin. Results showed that the BCG approach allows a more reliable way to determine the ecological status of streams in the Ceyhan River Basin by combining biological and chemical assessments for the sustainability of the environment. It is recommended that the BCG will be applied and evaluated in future research studies across various river basins, both within and outside of Turkey.

Information synthesis to identify water quality issues and select applicable in-stream water quality model for the Awash River basin in Ethiopia: A perspective from developing countries

In the sub-Saharan countries, stream water quality is declining due to many human activities. In-stream water quality models help to prepare effective planning strategy to tackle the problem and understand pollutant dynamics in the stream system. In this study, water quality issues of the Awash basin were reviewed to select an applicable in-stream model. The key sources of pollutants were considered and the availability, appropriateness and quality of related data were assessed and the capacity of model users was also evaluated. The identified opportunities and limitations were analyzed to present options of applicable models simulating the status quo in the basin's streams, and also, the changes needed for the existing settings. The model selection was done using a set of criteria based on assumptions useful for enabling environment and improvement in the future. Land covers, surficial geologies, and urban and industries along streams are found major issues to be addressed. Though the poor capacity of the governmental model users is a concern, the available hydrological, monitoring, and meteorological information are opportunities to capitalize the usage of in-stream modeling. QUAL2KW and INCA models are found more applicable for the present conditions, while in the future the WASP model may well be useful to conduct detailed analysis. The identification process applied in this study is based on the context of the Awash basin and it can be a replicated and support local model practitioners in creating improvement in water quality managements.

Pink salmon productivity is driven by catchment hydrogeomorphology and can decline under a changing climate

Abstract Increased flood magnitude and frequency due to climate change can reduce the population productivity of organisms such as amphibian and fish species in river and stream systems; therefore, conserving habitats that maintain high productivity under such conditions is crucial. Here, we examined the relationship between the freshwater productivity of anadromous salmonids (measured as fry migrating to the ocean per spawner) and catchment hydrogeomorphology and identified the characteristics of rivers and streams that are prone to flood disturbance. We surveyed the spawner abundance and number of fry of pink salmon (Oncorhynchus gorbuscha) and measured environmental factors, including the average catchment slope and stream power, as characteristics of hydrogeomorphology, in 10 streams in the Shiretoko Peninsula, northern Japan. We then used generalised linear mixed models to predict the freshwater productivity of pink salmon populations in each catchment across the study region under current and future climatic conditions. The productivity of pink salmon in the study region differed among the sampled catchments and was negatively affected by the average catchment slope, stream power, and maximum daily precipitation averaged over the catchment. Namely, flood disturbance reduced the freshwater productivity of pink salmon, and salmon productivity in individual catchments was explained by catchment hydrogeomorphology. The predicted future productivity with increased precipitation was also lower than the current productivity. Our approach can be applied to other salmonids that have similar spawning behaviour to pink salmon. Highly productive catchments under the future climatic conditions predicted by the present study should be prioritised for conservation to ensure a sustainable salmonid population.

Academic Success at Social Costs: An Exploratory Study on Social Networks of Chinese Students under Academic Streaming.

In universities that require students to reside in dormitories, there are two types of social networks-study/classroom-based and social/dorm room-based. The academic streaming system may disrupt study/classroom connections, but its impact on students' social networks is unknown. Using self-reported surveys, this study examines ego network measures of network sizes, turnover, multiplexity, and diversity among 382 students (44% female, 56% male). Surveys were administered before and after the university employed a first-semester grade-point average to demote or promote students into an honours college. Follow-up interviews were conducted with 11 honours students staying within their track and 11 students who were re-streamed to the non-honours track. Quantitative results showed that students in the non-honours college and who remained there had increasingly overlapping friendship circles between study and social environments, along with more diverse social connections, indicating stronger networks. In contrast, honours participants experienced fewer overlapping networks across domains and less dispersed social ties, especially after the academic replacement process. Qualitative results showed that the honours students faced a trade-off between academic success and social engagement in maintaining their elite status. Re-streamed students experienced otherness in social groups and decreased psychological wellbeing. This study contributes to the application of network analysis in education and provides insights into the unintended consequences of educational practice on students' social networks.

Movements of platypuses around and through instream structures and natural barriers in the Jenolan Karst Conservation Reserve, New South Wales

Severe flooding in early 2020 and 2021 necessitated major desedimentation works at the iconic Blue Lake in the Jenolan Karst Conservation Reserve (JKCR). Movements and behaviour of platypuses were monitored before, during and after these works, using direct observations, remote cameras and environmental DNA (eDNA) sampling. Platypuses were observed along a 3 km reach of the Jenolan River, including the areas where works occurred, although in low numbers. In their use of the available waterways, platypuses negotiated artificial barriers, including a 10 m high dam, two smaller weirs and natural waterfalls and cascades. Overland movements were detected through vegetation tunnels, drainage pipes and culverts, and individuals were seen entering the cave system, where eDNA was also detected. Platypuses responded to the works activity by foraging outside the affected areas but also continued to traverse these areas from time to time. We describe movements around and through instream infrastructure and past natural barriers and report on other species detected by remote cameras. These observations could help planning and deployment of bypasses suitable for movement of platypuses around anthropogenic barriers and provide insights into impediments to dispersal and gene flow within stream systems.

Pricing and service effort strategy in live streaming commerce supply chain under the equal proportion settlement mode.

Investigating novel collaboration modes is imperative for enhancing the cooperative ties between brand retailers and anchors as live streaming commerce moves progressively towards standardization. In this paper, we study a live streaming commerce supply chain system composed of a brand retailer and an Internet celebrity anchor. We also develop the pricing and live streaming service effort decision models under the equal proportion settlement mode of pit fee for the brand retailer and anchor. The research results show that under certain conditions, there is an optimal joint decision on price discount and live streaming service effort. In addition, the equal proportion settlement mode provides security for brand retailers but tends to expose the anchor's capabilities of live streaming sales. Consequently, anchors can only obtain a higher proportion of the pit fee by putting in more effort. Finally, through numerical analysis, we presented the impact of key parameters on the optimal decisions, demand, and profits of brand retailers and anchors. Based on these findings, we provided relevant managerial insights, offering valuable guidance and reference for the live streaming commerce industry.

CrossNet: Cross-scene Background Subtraction Network via 3D Optical Flow

This paper investigates an intriguing yet unsolved problem of cross-scene background subtraction for training only one deep model to process large-scale video streaming. We propose an end-to-end cross-scene background subtraction network via 3D optical flow, dubbed CrossNet. First, we design a new motion descriptor, hierarchical 3D optical flows (3D-HOP), to observe fine-grained motion. Then, we build a cross-modal dynamic feature filter (CmDFF) to enable the motion and appearance feature interaction. CrossNet exhibits better generalization since the proposed modules are encouraged to learn more discriminative semantic information between the foreground and the background. Furthermore, we design a loss function to balance the size diversity of foreground instances since small objects are usually missed due to training bias. Our whole background subtraction model is called Hierarchical Optical Flow Attention Model (HOFAM). Unlike most of the existing stochastic-process-based and CNN-based background subtraction models, HOFAM will avoid inaccurate online model updating, not heavily rely on scene-specific information, and well represent ambient motion in the open world. Experimental results on several well-known benchmarks demonstrate that it outperforms state-of-the-art by a large margin. The proposed framework can be flexibly integrated into arbitrary streaming media systems in a plug-and-play form. Codes are available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/dongzhang89/HOFAM</uri> .