Stream Processes Research Articles

SUV OMBORLARIDA LOYQA BOSISH JARAYONINI ZAMONAVIY TEXNOLOGIYALAR YORDAMIDA BAHOLASH

Once dams are built, sediments start to accumulate in the upper bay waters, filling the dead layer, which leads to blurring of clear waters and lowered efficiency of the reservoir. Finding a solution to this problem has been one of the main objectives for the scientists across the globe. Quite a few studies have been made to-date, in view to investigate deformation processes in upper bay waters, as well as to measure the sedimentation volume using field-based data. Enhancing the tools available for measuring hydrological processes in upper streams of water treatment facilities, using the latest scientific achievements in the field, as well as developing mechanisms ensuring less water loss are recognized as the most important goals nowadays. In this regard, the issues of enhanced exploitation reliability of reservoirs as well as of lower rates of turbidity and elaboration of effective tools for measuring

Transfer learning for mobile real-time face mask detection and localization.

ObjectiveDue to the COVID-19 pandemic, our daily habits have suddenly changed. Gatherings are forbidden and, even when it is possible to leave the home for health or work reasons, it is necessary to wear a face mask to reduce the possibility of contagion. In this context, it is crucial to detect violations by people who do not wear a face mask.Materials and MethodsFor these reasons, in this article, we introduce a method aimed to automatically detect whether people are wearing a face mask. We design a transfer learning approach by exploiting the MobileNetV2 model to identify face mask violations in images/video streams. Moreover, the proposed approach is able to localize the area related to the face mask detection with relative probability.ResultsTo asses the effectiveness of the proposed approach, we evaluate a dataset composed of 4095 images related to people wearing and not wearing face masks, obtaining an accuracy of 0.98 in face mask detection.Discussion and ConclusionThe experimental analysis shows that the proposed method can be successfully exploited for face mask violation detection. Moreover, we highlight that it is working also on device with limited computational capability and it is able to process in real time images and video streams, making our proposal applicable in the real world.

Strategies of shredders when feeding on low‐quality leaf‐litter: Local population adaptations or fixed species traits?

AbstractThe linkage between leaf‐litter and macroinvertebrate shredders is pivotal for stream food webs. Global change is predicted to decrease the nutritional quality of litter inputs to streams. However, little is known about shredder's ability to develop local interpopulation adaptations to face nutrient‐depleted leaf‐litter. We hypothesized that this adaptation could be present in populations receiving low‐quality leaf‐litter. We performed feeding tests on three abundant shredders species from lowland (a snail) and mountain (two insects) streams. Two populations of each species were derived from two subregions contrasting in average quality of litter inputs. Individuals were fed on four diets of contrasting quality: two leaf‐litter species with two qualities each, and their feeding rates, survivorship, growth, and energetic storage were evaluated. Results suggest that local population adaptation to low‐quality litters is not common, being essentially a fixed species trait that varies across species, in particular among snails and insects. The ability of the snail to cope with low‐quality litters suggests that ecosystem processes in lowland streams may resist reductions in litter quality. Conversely, potential alterations of riparian vegetation linked to global changes might disrupt mountain stream ecosystem functioning.

Overlooked Implication of Sediment Transport at Low Flow: Migrating Ripples Modulate Streambed Phototrophic and Heterotrophic Microbial Activity

AbstractSandy streambeds are mobile even at low flow velocities at which sediments can be transported as bedload, more specifically as migrating ripples. Small variations in discharge can result in transitions between sediment transport and no‐transport. Despite being inherent processes of streams and rivers, the effect of sediment transport and transport regime transition on the phototrophic and heterotrophic activity of streambed microbial communities remains unclear. We performed a microcosm experiment mimicking sediment transport as migrating ripples (i.e., migrating) and no sediment transport (i.e., stationary), and their transition to observe the response of the phototrophic and heterotrophic microbial community. Both net community production and community respiration were respectively 77% and 40% suppressed in migrating sediments compared to stationary sediments. In migrating sediments, a combination of mechanical stress, light limitation, and limited habitable area likely hampered microbial metabolism. Stationary conditions facilitated an active community of phototrophs, mainly diatoms, as indicated by high net community production, high rates of dissolved organic carbon release and silicon retention. After transitioning migrating to stationary and vice versa, differences were maintained regardless of the change in mechanical stress and associated stressors, most likely as a result of the interaction between their antecedent transport conditions and developmental stage that shaped the microbial community. Our results indicate that sediment transported as migrating ripples at low flow velocity can strongly modulate streambed metabolism, and discharge oscillations resulting in sediment transport transitions will result in a mosaic of microbial activity and biomass that will emerge at larger scales determining reach‐scale metabolism.

Taxonomic and functional turnover of Amazonian stream fish assemblages is determined by deforestation history and environmental variables at multiple scales

Abstract High rates of deforestation, either in the past or the present, affect many of the ecological processes in streams. Integrating deforestation history and the current landscape structure enhances the evaluation of ecological effects of land-use change. This is especially true when contemporary landscape conditions are similar but the temporal path to those conditions differs. One approach that has shown promise for evaluating biodiversity responses over time and space is the β-diversity partitioning, which combines taxonomic and functional trait-based approaches. We tested hypotheses related to stream fish assemblages’ turnover in watersheds with different environmental conditions and deforestation histories. We sampled fish from 75 watersheds in the Machado River basin, Brazil, and environmental factors were quantified at multiple scales. Taxonomic turnover was higher than expected by chance, whereas functional turnover was lower than expected by the observed taxonomic turnover, indicating that deterministic processes are structuring these assemblages. The turnover, and the environmental factors differed among watersheds with different deforestation histories. Besides being scale-dependent, turnover patterns are also likely dependent on land use dynamics and involve time-lags.

An approach to integrating sustainability management parameters and indicators into value stream mapping

Sustainability is addressed in many ways in production research, and it is often coupled with Value Stream Mapping (VSM), a widely used technique for optimizing production systems utilizing lean concepts. The majority of writers in scientific literature offer systems for rating manufacturing processes (e.g. ratios, benchmarks). These methods are designed to decrease the quantity of (material) input required to produce a given number of products. As a result, better value stream goal conditions may be created to boost ecological efficiency and, as a result, lower costs. The primary goal of this work, however, is to provide a method for combining widely recognized sustainability metrics and indicators with VSM. Process-oriented accounting of resource consumption through buffers, transports, and processes along value streams underpins this method. This approach of incorporating sustainability into VSM adheres to internationally recognized standards for preventing input resource disposal via reuse, recycling, and recovery. On the one hand, this approach can be used for sustainability reporting by following international guidelines and frameworks, such as calculating emitted solvents per produced part, kilogram carbon dioxide equivalents per produced part (with units [kgCDE] or [kgCO2eq]), kilogram disposals per produced part, and so on. Companies, on the other side, will be able to assess the expenses and profits of sustainable value streams, allowing them to monetize their efforts and benefits. As a result, it is essential to get immersed in material flows in the value stream, material consumptions at processes, transportation energy consumption, buffers and processes in the value stream, process linkage with scrap rates, waste generation, and so on. To express the characteristics and indicators of sustainability, new data lines in VSM must be established. A use case from the automobile sector will be used to demonstrate the study results.

An EWMA control chart for the mean of individual streams in multiple stream processes

Abstract: In a multiple stream process (MSP) a product is manufactured in a number of streams in parallel. The traditional tool for monitoring MSPs, the group control chart (GCC), does not take into account that typically the value of the quality variable in each stream is the sum of a component common to all streams and an individual component, of the particular stream. This may render the GCC ineffective in detecting shifts in the mean of individual streams. Based on this two-components model, we propose an exponentially weighted moving average (EWMA) GCC to monitor the means of the individual streams components. We optimize its design (minimizing the ARL for given shifts in the mean of a stream) and compare their ARLs with the ones of other existing charts devised for two-components MSPs. For this comparison, we needed to obtain optimal designs of these previous charts too, which were not available in the literature; this is an additional contribution of our work. The ARLs of the charts were obtained by simulation, with a number of runs sufficiently large to ensure precise results. The results show that the proposed chart outperforms the previous ones, becoming thus recommended for the statistical control of MSPs.

Influence of Drying and Wildfire on Longitudinal Chemistry Patterns and Processes of Intermittent Streams

Stream drying and wildfire are projected to increase with climate change in the western United States, and both are likely to impact stream chemistry patterns and processes. To investigate drying and wildfire effects on stream chemistry (carbon, nutrients, anions, cations, and isotopes), we examined seasonal drying in two intermittent streams in southwestern Idaho, one stream that was unburned and one that burned 8 months prior to our study period. During the seasonal recession following snowmelt, we hypothesized that spatiotemporal patterns of stream chemistry would change due to increased evaporation, groundwater dominance, and autochthonous carbon production. With increased nutrients and reduced canopy cover, we expected greater shifts in the burned stream. To capture spatial chemistry patterns, we sampled surface water for a suite of analytes along the length of each stream with a high spatial scope (50-m sampling along ~2,500 m). To capture temporal variation, we sampled each stream in April (higher flow), May, and June (lower flow) in 2016. Seasonal patterns and processes influencing stream chemistry were generally similar in both streams, but some were amplified in the burned stream. Mean dissolved inorganic carbon (DIC) concentrations increased with drying by 22% in the unburned and by 300% in the burned stream. In contrast, mean total nitrogen (TN) concentrations decreased in both streams, with a 16% TN decrease in the unburned stream and a 500% TN decrease (mostly nitrate) in the burned stream. Contrary to expectations, dissolved organic carbon (DOC) concentrations varied more in space than in time. In addition, we found the streams did not become more evaporative relative to the Local Meteoric Water Line (LMWL) and we found weak evidence for evapoconcentration with drying. However, consistent with our expectations, strontium-DIC ratios indicated stream water shifted toward groundwater-dominance, especially in the burned stream. Fluorescence and absorbance measurements showed considerable spatial variation in DOC sourcing each month in both streams, and mean values suggested a temporal shift from allochthonous toward autochthonous carbon sources in the burned stream. Our findings suggest that the effects of fire may magnify some chemistry patterns but not the biophysical controls that we tested with stream drying.

Influence of Aquatic Vegetation on Dispersive Parameters as a Part of Hydrodynamic Conditions in Natural Streams

Submerged and emergent aquatic vegetation is a natural and organic component of natural rivers and streams. It plays an important role in all physical, chemical and biological processes in the stream biocoenosis. This type of vegetation has also a non-negligible impact on flow conditions. It influences the discharge, hydraulic roughness, velocity as well as other hydraulic parameters. Important part of the river hydrodynamic processes are also dispersive processes and its parameters, which defines the speed and intensity of the dispersive processes in the natural stream. This paper analyses these aspects of the stream hydrodynamics, which are influenced by aquatic vegetation and analyses the influence of the submerged and emerged vegetation on mixing processes in a river. Presented results are findings of hydrometric measurements and tracer experiments at the Šúrsky kanál stream, located in south-west part of Slovakia. The Šúrsky kanál stream is a typical lowland stream, where significant changes in the vegetation are present during different periods of a year. The hydrometric and tracer experiments were performed on 1700 m long straight reach of the stream with a relatively prismatic cross-section profile during the growing as well as non- growing season of a year. The results show, that the level of vegetative growth has a significant influence on the hydrodynamic parameters of the stream, as well as on the dispersive process. The dispersive process is influenced not only by the velocity and concentration gradients, but also by the fact that the vegetation forms in the stream so-called dead zones. Such dead zones modify the velocity profiles of a stream and affect dispersive mass transport within the stream by collecting and separating parts of the tracer from the main current. Subsequently, the tracer is slowly released and incorporated back to the main current in a stream. This process deforms the shape of the tracer concentration distribution in time. All these facts were confirmed by the experiments results described in this paper, which contains also the analysis of the dead zones effect on the dispersive process.

Performance characterization of X group control charts

Group control charts are used for the statistical control of multiple stream processes. Recently, a modified control chart based on the residuals from each stream has been proposed as an alternative charting scheme. This research examines the performance of these charts under varying combinations of shift magnitudes and number of streams affected. Several simulated scenarios were generated and used to evaluate the long-term performance of the two schemes in terms of the average run length. Statistical analysis of the results indicated that the modified chart has an advantage over the traditional group chart in terms of the rate of false alarms. However, both charting schemes appear to have similar shift detection capabilities.

Quality indicator of the smart city transportation and logistics system

Subject. The article considers functioning and development of process flows of transportation and logistics system of a smart city. Objectives. The study identifies factors and dependencies of the quality of human life on the organization and management of stream processes. Methods. I perform a comparative analysis of previous studies, taking into account the uniquely designed results, and the econometric analysis. Results. The study builds multiple regression models that are associated with stream processes, highlights interdependent indicators of temporary traffic and pollution that affect the indicator of life quality. However, the identified congestion indicator enables to predict the time spent in traffic jams per year for all participants of stream processes. Conclusions. The introduction of modern intelligent transportation systems as a component of the transportation and logistics system of a smart city does not fully solve the problems of congestion in cities at the current rate of urbanization and motorization. A viable solution is to develop cooperative and autonomous intelligent transportation systems based on the logistics approach. This will ensure control over congestion, the reduction of which will contribute to improving the life quality of people in urban areas.

The alternative distribution of the non parametric extended median test CUSUM chart for multiple stream processes

When monitoring a multiple stream process (MSP) where multiple processes which are assumed to be identical are being simultaneously monitored, but the assumption of normality cannot be reasonably be verified, the NEMT-CUSUM control chart has been proposed as a possible non parametric alternative. However, in the beginning stages of a monitoring program, it would be useful to the chart operator to know how effective the NEMT-CUSUM will be at detecting shifts away from target given. One way of assessing effectiveness is via statistical power, which is the probability of detecting a shift in some subset of streams at a particular point in time. The purpose of this study is to derive the alternative distribution of the NEMT-CUSUM plotting statistic such that statistical power can be estimated. Examples, practical implications, and future directions are given.

Litter decomposition in Afrotropical streams: Effects of land use, home-field advantage, and terrestrial herbivory

AbstractLand use can strongly affect litter decomposition, a key ecosystem process in low-order streams. Recent evidence suggests that additional drivers of decomposition rates may include: 1) home...

Biochemical and functional responses of stream invertebrate shredders to post-wildfire contamination

Forests in Mediterranean Europe including Portugal are highly susceptible to wildfires. Freshwaters are often exposed to post-wildfire contamination that contains several toxic substances, which may impose risk to freshwater organisms and ecosystem functions. However, knowledge on the impacts of post-wildfire runoffs from different origins on freshwater biota is scarce. In forest streams, invertebrate shredders have a major contribution to aquatic detrital-based food webs, by translocating energy and nutrients from plant-litter to higher trophic levels. We investigated the leaf consumption behaviour and the responses of oxidative and neuronal stress enzymatic biomarkers in the freshwater invertebrate shredder Allogamus ligonifer after short-term exposure (96 h) to post-wildfire runoff samples from Pinus and Eucalyptus plantation forests and stream water from a burnt catchment in Portugal. Chemical analyses indicated the presence of various metals and PAHs at considerable concentrations in all samples, although the levels were higher in the runoff samples from forests than in the stream water. The shredding activity was severely inhibited by exposure to increased concentrations of post-wildfire runoff samples from both forests. The dose-response patterns of enzymatic biomarkers suggest oxidative and neuronal stress in the shredders upon exposure to increasing concentrations of post-wildfire runoffs. The impacts were more pronounced for the runoffs from the burnt forests. Moreover, the response patterns suggest that the energy from the feeding activity of shredders might have contributed to alleviate the stress in A. ligonifer. Overall, the outcomes suggest that the post-wildfire contamination can induce sublethal effects on invertebrate shredders with impacts on key ecological processes in streams.

Coupling wavelet transform with multivariate adaptive regression spline for simulating suspended sediment load: Independent testing approach

ABSTRACT Accurate prediction of suspended sediment load (SSL) of a river is very important as it directly affects the performance of the corresponding hydraulic structures. SSL can give valuable information on the catchment erodibility and deposition of the sediment being produced through scouring phenomenon. Despite the hydraulic approaches for studying the scouring/sedimentation processes in streams, hydrologic approaches may provide valuable information about SSL deposition magnitudes as well as its temporal distribution in relation with the streamflow power. A hydrologic-based approach through coupling the wavelet-based processed signals and multi adaptive regression spline (WMARS) methodology is suggested in the present paper for the first time to predict SSL values of rivers using the simultaneous streamflow and SSL records. The developed models were assessed through the most powerful k-fold testing data scanning procedure. The obtained results showed the superiority of the proposed hybrid WMARS models over the single MARS and traditional sediment rating curve techniques. Due to the presence of hysteresis effects during the study periods, adaptation of k-fold testing assessment approach is very necessary to get better insight about the models performances.

Combined effects of freshwater salinization and leaf traits on litter decomposition

Freshwater salinization is a matter of major global concern due to its consequences on the aquatic biota and ecosystems functioning. Salt contamination negatively affects the leaf litter decomposition process, a key ecosystem-level process in forested streams that contributes to the recycling of nutrients and carbon storage. However, information on how additional factors may influence the magnitude of the response to salinization is scarce. In this microcosm study we assessed the importance of leaf (Castanea sativa; Quercus robur) traits, on aquatic hyphomycetes-mediated leaf litter decomposition and associated variables, in salt-contaminated (0, 1, 3 and 6 g/l NaCl) environments. The leaves were incubated individually, and in a mixture, for 28 days, under each tested salt concentration. Salinity depressed leaf mass loss, fungal biomass, respiration and sporulation rates, particularly at the highest salt concentration. Differences across leaf categories were observed in all parameters but fungal biomass, although the effects were not consistent across descriptors. All leaf categories responded with a similar intensity to salt contamination for all measured variables but sporulation rate. These results suggest that the deleterious influence of salt on litter decomposition occurs independently of the traits of the stream riparian subsidies.

Direct measurement of secondary circulation in a meandering macrotidal estuary

Secondary circulation, which induces the typical helical flow motion along a curved channel, is responsible for the complex morphodynamic processes in fluvial streams and estuaries with meandering nature. Classical secondary circulation has been extensively documented through flume experiments and numerical simulations but field observations about this phenomenon are scarce and only limited to few channel cross-sections. In this study, intensive measurements of flow velocities were performed using a vessel-mounted ADCP in order to illustrate the spatial distribution of classical secondary circulation in a meandering macrotidal estuary for both flood and ebb phases. Negligible salinity is noted during field measurements and velocity profiles manifesting logarithmic patterns confirm open channel flow conditions. As the flow enters the bend, primary and secondary velocities are shifted towards the outer bank. At the bend apex, circulation is accelerated with near-surface primary and secondary velocities skewed to the outer bank while bottom currents are skewed to the inner bank. As the flow exits the bend, bottom secondary currents gain dominance over surface currents while the bottom velocity vectors are directed towards the inner bank. Both the primary and secondary currents cause the propagation of the three-dimensional helical flow alongside with the asymmetry in the bend cross-section and the formation of point bar. This study successfully pioneers in demonstrating the three-dimensional structure of classical secondary circulation in actual field conditions through intensive ADCP surveys.

Machine learning for predictive scheduling and resource allocation in large scale manufacturing systems

The digitalization processes in manufacturing enterprises and the integration of increasingly smart shop floor devices and software control systems caused an explosion in the data points available in Manufacturing Execution Systems. The degree in which enterprises can capture value from big data processing and extract useful insights represents a differentiating factor in developing controls that optimize production and protect resources. Machine learning and Big Data technologies have gained increased traction being adopted in some critical areas of planning and control. Cloud manufacturing allows using these technologies in real time, lowering the cost of implementing and deployment. In this context, the paper offers a machine learning approach for reality awareness and optimization in cloud.Specifically, the paper focuses on predictive production planning (operation scheduling, resource allocation) and predictive maintenance. The main contribution of this research consists in developing a hybrid control solution that uses Big Data techniques and machine learning algorithms to process in real time information streams in large scale manufacturing systems, focusing on energy consumptions that are aggregated at various layers. The control architecture is distributed at the edge of the shop floor for data collecting and format transformation, and then centralized at the cloud computing platform for data aggregation, machine learning and intelligent decisions. The information is aggregated in logical streams and consolidated based on relevant metadata; a neural network is trained and used to determine possible anomalies or variations relative to the normal patterns of energy consumption at each layer. This novel approach allows for accurate forecasting of energy consumption patterns during production by using Long Short-term Memory neural networks and deep learning in real time to re-assign resources (for batch cost optimization) and detect anomalies (for robustness) based on predicted energy data.

Variable temperature effects between heterotrophic stream processes and organisms

Abstract Temperature is known to stimulate metabolism with cascading effects on multiple biological processes. These effects may, however, vary across processes, types of organisms or levels of biological organisation. They can also vary with nutrient availability, with potentially stronger temperature effects when nutrients are not limiting. This context dependence of temperature effects on processes challenges our ability to anticipate their consequences on ecosystems in a changing world. In headwater streams, the decomposition of allochthonous leaf litter, driven by both microbial decomposers and invertebrates, is known to respond to both temperature and nutrient availability. These food webs are highly tractable and a useful model system to investigate the variations of temperature effects on processes across types of organisms (microbes versus invertebrates), resource availability levels (nutrient concentration), and levels of biological organisation (from individual to ecosystem). In a microcosm experiment, we measured the effects of temperature and nitrogen availability (four levels each) on respiration rates of litter-consuming microbes and invertebrates and their decomposition activity in different contexts of food web complexity. The latter included one treatment without invertebrate detritivore (microbial decomposers only), three single invertebrate taxa (Gammarus, Potamophylax, and Sericostoma) treatments, and one mixed invertebrate taxa treatment (three‐species altogether). Microbial processes increased nearly exponentially with temperature (Arrhenius model, activation energy (± 95% confidence interval) = 0.56 ± 0.53 and 1.00 ± 0.23 eV for litter decomposition and respiration), while invertebrate‐driven processes increased (activation energy from 0.47–1.15 eV) up to a maximal value at an intermediate temperature (c. 11–15°C depending on species and process), above which process rates decreased. By contrast, litter consumption in mixed invertebrate species treatments was not significantly influenced by temperature, because of a negative effect of species mixing occurring above 12°C. Nitrogen had a weaker influence, only slightly stimulating litter consumption by mixed‐species invertebrates, which limited the scope for synergies with temperature effects. Our results raise issues about how aquatic litter consumers meet their energy requirements at high temperature and suggest that a general consequence of warming could be loss of carbon through mineralisation in headwater stream food webs. In several aspects, our results deviate from expectations based on universal relationships between temperature and individual metabolism (e.g. metabolic theory of ecology), suggesting that we may need to develop less simplistic assumptions to predict the consequence of warming on ecosystem processes.

Investigating the Flow Hydrodynamics in a Compound Channel with Layered Vegetated Floodplains

In natural rivers, vegetation grows on floodplains, generating complex velocity field within the compound channel. The efficient modelling of the flow hydraulics in a compound channel with vegetated floodplains is necessary to understand and determine the natural processes in rivers and streams. As the three dimensional (3D) flow features are difficult to capture through experimental investigation; therefore, the present numerical study was carried out to investigate the complex 3D flow structures with the vertically layered vegetation placed over the floodplains in a symmetric trapezoidal compound channel. The simulations were conducted using a Computational Fluid Dynamics (CFD) code FLUENT, whereas a Reynolds Averaged Navier-Stokes (RANS) technique based on Reynolds stress model (RSM) was implemented for turbulence closure. The numerical model successfully replicated the flow behavior and showed a good agreement with the experimental data. The present study concluded the presence of quite-S shaped velocity profile in the layered vegetated floodplains when the short vegetation was submerged during high flows or floods, whereas the velocity profile was uniform or almost logarithmic during low floods or when both short and tall vegetation remained emergent. The lateral exchange of mass and momentum was promoted due to the flow separation and instability along the junction of the floodplains and main channel. The flow velocities were significantly reduced in the floodplains due to resistance offered by the vegetation, which consequently resulted in an increased percentage i.e. 67-73%, of passing discharge through the main channel. In general, the spatial distribution of mean flow and turbulence characteristics was considerably affected near the floodplain and main channel interfaces. Moreover, this study indicated a positive flow response for the sediment deposition as well as for the nourishment of the aquatic organisms in the riparian environment.