Flow-based Method Research Articles

Chip-Based Spectrofluorimetric Determination of Iodine in a Multi-Syringe Flow Platform with and without In-Line Digestion-Application to Salt, Pharmaceuticals, and Algae Samples.

In this work, a flow-based spectrofluorimetric method for iodine determination was developed. The system consisted of a miniaturized chip-based flow manifold for solutions handling and with integrated spectrofluorimetric detection. A multi-syringe module was used as a liquid driver. Iodide was quantified from its catalytic effect on the redox reaction between Ce(IV) and As(III), based on the Sandell–Kolthoff reaction. The method was applied for the determination of iodine in salt, pharmaceuticals, supplement pills, and seaweed samples without off-line pre-treatment. An in-line oxidation process, aided by UV radiation, was implemented to analyse some samples (supplement pills and seaweed samples) to eliminate interferences and release iodine from organo-iodine compounds. This feature, combined with the fluorometric reaction, makes this method simpler, faster, and more sensitive than the classic approach of the Sandell–Kolthoff reaction. The method allowed iodine to be determined within a range of 0.20–4.0 µmol L−1, with or without the in-line UV digestion, with a limit of detection of 0.028 µmol L−1 and 0.025 µmol L−1, respectively.

An alternative flow cytometry based approach to measuring cell proliferation

Background: Lymphocyte proliferation in vitro assays are used in the assessment of primary immunodeficiency disorders and monitoring for recovery of T-cell function following hematopoietic stem cell transplant. Previously established assay methods have used radioactive tritiated thymidine with attendant logistic and safety issues. Alternative methods which do not require the use of radioactive materials include flow cytometry-based techniques. Herein, a flow-based method using violet proliferation dye 450 (VPD450) was assessed for feasibility and clinical utility in the diagnostic immunology laboratory.

Towards real-time tracking and counting of seedlings with a one-stage detector and optical flow

The population of crop seedlings is important for breeders and growers to evaluate the emergence rate of different cultivars and the necessity of replanting, but manual counting of plant seedlings is time-consuming and tedious. Building upon our prior work, we advanced the cotton seedling tracking method by incorporating a one-stage object detection deep neural network and optical flow to improve tracking speed and counting accuracy. Videos of cotton seedlings were captured using consumer-grade video cameras from the top view. You Only Look Once Version 4 (YOLOv4), a one-stage object detection network, was trained to detect cotton seedlings in each frame and to generate bounding boxes. To associate the same seedlings between adjacent frames, an optical flow-based tracking method was adopted to estimate camera motions. By comparing the positions of bounding boxes predicted by optical flow and detected by the YOLOv4 network in the same frame, the number of cotton seedlings was updated. The trained YOLOv4 model achieved high accuracy under conditions of occlusions, blurry images, complex backgrounds, and extreme illuminations. The F1 score of the final detection model was 0.98 and the average precision was 99.12%. Important tracking metrics were compared to evaluate the tracking performance. The Multiple-Object Tracking Accuracy (MOTA) and ID switch of the proposed tracking method were 72.8% and 0.1%, respectively. Counting results showed that the relative error of all testing videos was 3.13%. Compared with the Kalman filter and particle filter-based methods, our optical flow-based method generated fewer errors on testing videos because of higher accuracy of motion estimation. Compared with our previous work, the RMSE of the optical flow-based method decreased by 0.54 and the counting speed increased from 2.5 to 10.8 frames per second. The counting speed can reach 16.6 frames per second if the input resolution was reduced to 1280 × 720 pixels with an only 0.45% reduction in counting accuracy. The proposed method provides an automatic and near real-time tracking approach for counting of multiple cotton seedlings in video frames with improved speed and accuracy, which will benefit plant breeding and precision crop management.

Practical implementation of a method for global single-phase flow-based transmissibility upscaling using generic flow boundary conditions and its application on models with non-local heterogeneities

Local upscaling techniques fall short in capturing the dynamic effects of laterally continuous non-local geologic heterogeneities, for example, high-permeability channels, vertically thin, yet, horizontally extensive shale layers. Global upscaling techniques have been introduced to remedy the shortcomings of local scale-up approaches. In order to address the upscaling challenges associated with non-local heterogeneities, we have developed a practical and effective flow-based transmissibility scale-up method that computes coarse-scale transmissibilities using flux derived from single-phase flow simulations with generic global boundary conditions, referred to as the global transmissibility upscaling (GTU) method. GTU targets more accurate upscaling of laterally continuous non-local heterogeneities including the ones modeled on distorted cornerpoint grids. A variant of GTU is developed in this context that uses fluxes computed by use of the multi-point flux approximation (MPFA) discretization technique at the fine scale. While various global upscaling methods were described in the literature, they are rarely used in industrial applications due to challenges related to implementation. We describe in detail an effective practical implementation of the GTU method in a comprehensive industrial-grade simulation package and share our learnings with GTU on aggressively upscaled models with non-local heterogeneities. We demonstrate the application of GTU to several challenging reservoir models. Comparisons of GTU-based model responses are made with ones stemming from local upscaling techniques popularly utilized in the industry using fine-scale model predictions as reference. Investigated numerical examples demonstrate that the GTU method leads to notable improvements in the accuracy delivered by coarse-scale models. Especially, the application of GTU is most impactful for high-upscaling-ratio models with complex fine-scale connectivity because GTU preserves the fine-scale behavior more authentically compared to local techniques. We demonstrate that GTU naturally complements an innovative regional multiphase upscaling (RMU) method on aggressively upscaled models with strong multiphase flow associated with displacement-type recovery mechanisms. It has also been observed that using MPFA on cornerpoint grids to obtain fine-scale fluxes for GTU gives rise to more accurate coarse-scale pressure behavior. We have also observed that GTU is especially effective when combined with a regional multiphase upscaling method for ultimate accuracy in simulations of displacement-based recovery mechanisms. • A practical global transmissibility upscaling method using global flows enables fast and accurate flow simulations. • Global transmissibility upscaling preserves the fine-scale information more authentically compared to local techniques. • Global transmissibility upscaling combined with regional multiphase upscaling for fast and accurate flow simulation. • Speed-up values in the order of 10–50 fold are achieved over fine-scale model with a good compromise of accuracy.

Uncovering spatial representations from spatiotemporal patterns of rodent hippocampal field potentials

SummarySpatiotemporal patterns of large-scale spiking and field potentials of the rodent hippocampus encode spatial representations during maze runs, immobility, and sleep. Here, we show that multisite hippocampal field potential amplitude at ultra-high-frequency band (FPAuhf), a generalized form of multiunit activity, provides not only a fast and reliable reconstruction of the rodent's position when awake, but also a readout of replay content during sharp-wave ripples. This FPAuhf feature may serve as a robust real-time decoding strategy from large-scale recordings in closed-loop experiments. Furthermore, we develop unsupervised learning approaches to extract low-dimensional spatiotemporal FPAuhf features during run and ripple periods and to infer latent dynamical structures from lower-rank FPAuhf features. We also develop an optical flow-based method to identify propagating spatiotemporal LFP patterns from multisite array recordings, which can be used as a decoding application. Finally, we develop a prospective decoding strategy to predict an animal's future decision in goal-directed navigation.

Estimation of aquitard hydraulic conductivity and skeletal specific storage considering non-Darcy flow

Darcy's law has been widely used to study the groundwater drainage process within an aquitard. However, non-Darcy flow is frequently encountered in laboratory and in situ investigations. With consideration of a sudden drop in boundary hydraulic heads, aquitard compaction characteristics and their sensitivities to the non-Darcy flow control variables were analyzed. The non-Darcy flow was found to retard groundwater drainage, and the retardation effects were much more significant at early-to-intermediate time points. Under this specific boundary condition, the time–compaction curve in a log–log graph at early time points was found to be close to a straight line, whose slope can be used to indirectly evaluate the extent of the non-Darcy effect. A non-Darcy flow-based type curve method was developed for estimating aquitard hydraulic conductivity (K) and skeletal specific storage (Ss), and this method was used to interpret the time–compaction data recorded in a laboratory experiment. The tested aquitard was determined to be associated with non-Darcy flow due to the fact that the time–compaction curve deviated from the Darcy's law-based theoretical curve. Darcy's law resulted in an underestimated K. In contrast, the estimated Ss was almost unaffected by the flow state, if the observation lasted long enough to reach final steady compaction.

A viability study of 3D tumor spheroids after their mass-density characterization via an innovative flow-based biophysical method

The simple measurement of mass density, size and weight of sphere-like 3D cell models has been recently enabled by a specifically conceived flow-based method. Here we demonstrate that such technique also allows the post-analysis collection of live 3D tumor spheroids, without compromising their viability.

Fast Local Flow-based Method using Parallel Multi-core CPUs Architecture

Fast Local Flow-based Method using Parallel Multi-core CPUs Architecture

Enhanced Solutal Marangoni Flow Using Ultrasound-Induced Heating for Rapid Digital Microfluidic Mixing

Digital microfluidics based on sessile droplets has emerged as a promising technology for various applications including biochemical assays, clinical diagnostics, and drug screening. Digital microfluidic platforms provide an isolated microenvironment to prevent cross-contamination and require reduced sample volume. Despite these advantages, the droplet-based technology has the inherent limitation of the quiescent flow conditions at low Reynolds number, which causes mixing samples confined within the droplets to be challenging. Recently, solutal Marangoni flows induced by volatile liquids have been utilized for sessile droplet mixing to address the above-mentioned limitation. The volatile liquid vaporized near a sessile droplet induces a surface tension gradient throughout the droplet interface, leading to vortical flows inside a droplet. This Marangoni flow-based droplet mixing method does not require an external energy source and is easy to operate. However, this passive method requires a comparably long time of a few tens of seconds for complete mixing since it depends on the natural evaporation of the volatile liquid. Here, we propose an improved ultrasound-induced heating method based on a nature-inspired ultrasound-absorbing layer and apply it to enhance solutal Marangoni effect. The heater consists of an interdigital transducer deposited on a piezoelectric substrate and a silver nanowire-polydimethylsiloxane composite as an ultrasound-absorbing layer. When the transducer is electrically actuated, surface acoustic waves are produced and immediately absorbed in the composite layer by viscoelastic wave attenuation. The conversion from acoustic to thermal energy occurs, leading to rapid heating. The heating-mediated enhanced vaporization of a volatile liquid accelerates the solutal Marangoni flows and thus enables mixing high-viscosity droplets, which is unachievable by the passive solutal Marangoni effect. We theoretically and experimentally investigated the enhanced Marangoni flow and confirmed that rapid droplet mixing can be achieved within a few seconds. The proposed heater-embedded sessile droplet mixing platform can be fabricated in small size and easily integrated with other digital microfluidic platforms. Therefore, we expect that the proposed sample mixing method can be utilized for various applications in digital microfluidics and contribute to the advancements in the medical and biochemical fields.

Targeted pandemic containment through identifying local contact network bottlenecks.

Decision-making about pandemic mitigation often relies upon simulation modelling. Models of disease transmission through networks of contacts-between individuals or between population centres-are increasingly used for these purposes. Real-world contact networks are rich in structural features that influence infection transmission, such as tightly-knit local communities that are weakly connected to one another. In this paper, we propose a new flow-based edge-betweenness centrality method for detecting bottleneck edges that connect nodes in contact networks. In particular, we utilize convex optimization formulations based on the idea of diffusion with p-norm network flow. Using simulation models of COVID-19 transmission through real network data at both individual and county levels, we demonstrate that targeting bottleneck edges identified by the proposed method reduces the number of infected cases by up to 10% more than state-of-the-art edge-betweenness methods. Furthermore, the proposed method is orders of magnitude faster than existing methods.

Scene image and human skeleton-based dual-stream human action recognition

The dual stream-based human action recognition model offers the advantage of high recognition accuracy, but the algorithm is less robust in case of lighting changes. The human skeleton has a strong ability to express human behavior and actions; however, the scene information is ignored. Drawing on the idea of the dual-stream model, this paper proposes a human skeleton and scene image-based dual-stream model for human action recognition. The motion features are extracted through the spatio-temporal graph convolution of the human skeleton, and a scene recognition model is proposed based on the sparse frame sampling of video and video-level consensus strategy to process the scene video and gather the visual scene information. The proposed model exploits the advantages of skeleton information in motion expression and the superiority of the image in scene presentation. The scene information and spatio-temporal graph convolution-based human skeleton limbs are fused complementarily to achieve human action recognition. Compared to the conventional optical flow-based dual-stream action recognition method, this model is verified by experimenting under unstable light conditions, and the performance of human action recognition is robust and promising.

Characteristics of Long-Duration Heavy Precipitation Events along the West Coast of the United States

AbstractProlonged periods (e.g., several days or more) of heavy precipitation can result in sustained high-impact flooding. Herein, an investigation of long-duration heavy precipitation events (HPEs), defined as periods comprising ≥3 days with precipitation exceeding the climatological 95th percentile, is conducted for 1979–2019 for the U.S. West Coast, specifically Northern California. An objective flow-based categorization method is applied to identify principal large-scale flow patterns for the events. Four categories are identified and examined through composite analyses and case studies. Two of the categories are characterized by a strong zonal jet stream over the eastern North Pacific, while the other two are characterized by atmospheric blocking over the central North Pacific and the Bering Sea–Alaska region, respectively. The composites and case studies demonstrate that the flow patterns for the HPEs tend to remain in place for several days, maintaining strong baroclinicity and promoting occurrences of multiple cyclones in rapid succession near the West Coast. The successive cyclones result in persistent water vapor flux and forcing for ascent over Northern California, sustaining heavy precipitation. For the zonal jet patterns, cyclones affecting the West Coast tend to occur in the poleward jet exit region in association with cyclonic Rossby wave breaking. For the blocking patterns, cyclones tend to occur in association with anticyclonic Rossby wave breaking on the downstream flank of the block. For Bering Sea–Alaska blocking cases, cyclones can move into this region in conjunction with cyclonically breaking waves that extend into the eastern North Pacific from the upstream flank of the block.

Diagnosis of Chikungunya Virus in Febrile Patients From a Malaria Holoendemic Area

IntroductionAccurate diagnosis of chikungunya (CHIK) is essential for effective disease management and surveillance. In a cohort of febrile Congolese patients, available diagnostic methods widely used in CHIK diagnosis were evaluated. In addition, plasma cytokines were quantified in CHIK patients and those coinfected with malaria compared with healthy controls. MethodsBetween June and November 2019, a total of 107 febrile patients with suspected CHIK were subjected to differential diagnosis both for CHIK and malaria. Patients were screened for CHIK virus using molecular diagnosis by real-time PCR, serologic testing by IgM-specific and IgG-specific ELISAs, and lateral flow-based method with rapid diagnostic test (RDT), while malaria diagnosis was confirmed by PCR methods. Pro-inflammatory (IL-12, IL-16, IFN-γ, TNF-α) and anti-inflammatory (IL-4, IL-10, IL-13) cytokines were quantified in patients and healthy controls by ELISA assays. ResultsMolecular diagnoses revealed that 57% (61/107) were positive for CHIK by RT-PCR, while serologic testing revealed 31% (33/107) and 9% (10/107) seropositivity for anti- IgM and IgG, respectively. None of the patients were CHIK RDT-positive. Also, 27% (29/107) were PCR-positive for malaria. Among the malaria-positive patients, 14% (15/107) were co-infected with CHIK and 13% (14/107) were monoinfection. Plasma IL-12 and TNF-α levels were increased in patients with malaria and IL-13 levels were increased in patients with co-infection (p<0.05). ConclusionCo-infection of malaria and CHIK were common in febrile Congolese patients. Real-time PCR was a better tool for detecting actual occurrences of CHIK in a malaria holoendemic area.

Numerical study of the Wavestar wave energy converter with multi-point-absorber around DeepCwind semisubmersible floating platform

The presented paper numerically studies on the Wavestar wave energy converter (WEC) with multi-point-absorber around the DeepCwind semisubmersible floating platform. The Wavestar concept is selected as suitable point absorbers in conduction with floating wind turbine supported by DeepCwind semisubmersible. The effects of the Wavestars mechanism on the power extraction and DeepCwind semisubmersible movement were investigated using the potential flow-based boundary element method (BEM) in ANSYS/AQWA software in time domain for two different wave incident angles. The DeepCwind semisubmersible floating wind turbine design was simulated, and the results were compared with the available experimental data. Uncoupled simulations in which the response amplitude operator (RAO) motions and fairlead tensions are prescribed according to the experimental data show relatively good agreement in fairlead tensions. Finally, various numbers of the Wavestars WEC of point absorbers are mounted around the DeepCwind semisubmersible. The numerical results of the surge, heave and pitch motions, absorbed power and wave contour under multi-point-absorber are presented and discussed.

A requirement for flow to enable the development of Ureaplasma parvum biofilms in vitro.

To use a flow-based method to establish, quantify and visualize biofilms of Ureaplasma parvum. Absorbance readings of a U.parvum HPA5 culture were taken at 550nm every 3h for 30h in order to establish a growth curve, with viability determined by the number of colour changing units (CCUs). Biofilms were established using the DTU flow-cell with a flow rate of 0·01mlmin-1 and compared to the static control. Titres of bacteria were determined by CCU and biofilm biomass was quantified by Syto9 staining and COMSTAT analysis. High-resolution images were obtained by scanning electron microscopy (SEM). Flow resulted in significantly more biofilm and higher cell titre (0·599µm3 /µm2 ±0·152 and 4×108 CCU per ml, respectively) compared with static conditions (0·008µm3 /µm2 ±0·010 and no recoverable cells, respectively). SEM revealed pleomorphic cells, with signs of budding and possible membrane vesicle formation. Flow is an essential requirement for the establishment of U.parvum biofilms. This is the first quantification of biofilm biomass formed by U.parvum. It is now possible to establish viable biofilms of U.parvum which will allow for future testing of antimicrobial agents and understanding of virulence-associated with adhesion.

Suitable CO2 Solubility Models for Determination of the CO2 Removal Performance of Oxygenators.

CO2 removal via membrane oxygenators during lung protective ventilation has become a reliable clinical technique. For further optimization of oxygenators, accurate prediction of the CO2 removal rate is necessary. It can either be determined by measuring the CO2 content in the exhaust gas of the oxygenator (sweep flow-based) or using blood gas analyzer data and a CO2 solubility model (blood-based). In this study, we determined the CO2 removal rate of a prototype oxygenator utilizing both methods in in vitro trials with bovine and in vivo trials with porcine blood. While the sweep flow-based method is reliably accurate, the blood-based method depends on the accuracy of the solubility model. In this work, we quantified performances of four different solubility models by calculating the deviation of the CO2 removal rates determined by both methods. Obtained data suggest that the simplest model (Loeppky) performs better than the more complex ones (May, Siggaard-Anderson, and Zierenberg). The models of May, Siggaard-Anderson, and Zierenberg show a significantly better performance for in vitro bovine blood data than for in vivo porcine blood data. Furthermore, the suitability of the Loeppky model parameters for bovine blood (in vitro) and porcine blood (in vivo) is evaluated.

A Continuous Sample Drop Flow-Based Microextraction Method for Spectrophotometric Determination of Cobalt with 1-(2-Pyridylazo)-2-Naphthol in Water Samples

There is always a need to develop new, fast and non-complicated microextraction methods that consume small amounts of organic solvents. In this study, a new mode of liquid phase microextraction method, termed as continuous sample drop flow-based microextraction (CSDF−ME), was developed for the enrichment and determination of cobalt in water samples. To attain the appropriate conditions for the CSDF−ME, experimental parameters such as pH, type and volume of extraction solvent, concentration of chelating agent, salting effect, sample flow rate and sample volume, needle diameter were examined. The enrichment factor was 167 for 20 mL sample solution. The calibration graph was linear in the concentration range of 5–200 μg/L with the correlation coefficient of 0.999. The limit of detection was 1.3 μg/L. The reliability of the recommended procedure was verified by analysis of real water samples (including tap, mineral and river water) and synthetic sample spiked with known amount of cobalt, and the obtained recoveries of spiked samples have demonstrated accuracy and applicability of the proposed method.

Flow-Based Attribution in Graphical Models: A Recursive Shapley Approach

We study the attribution problem in a graphical model, wherein the objective is to quantify how the effect of changes at the source nodes propagates through the graph. We develop a model-agnostic flow-based attribution method, called recursive Shapley value (RSV). RSV generalizes a number of existing node-based methods and uniquely satisfies a set of flow-based axioms. In addition to admitting a natural characterization for linear models and facilitating mediation analysis for non-linear models, RSV satisfies a mix of desirable properties discussed in the recent literature, including implementation invariance, sensitivity, monotonicity, and affine scale invariance.

Physical Characterization of Colorectal Cancer Spheroids and Evaluation of NK Cell Infiltration Through a Flow-Based Analysis.

To improve pathogenetic studies in cancer development and reliable preclinical testing of anti-cancer treatments, three-dimensional (3D) cultures, including spheroids, have been widely recognized as more physiologically relevant in vitro models of in vivo tumor behavior. Currently, the generation of uniformly sized spheroids is still challenging: different 3D cell culture methods produce heterogeneous populations in dimensions and morphology, that may strongly influence readouts reliability correlated to tumor growth rate or antitumor natural killer (NK) cell-mediated cytotoxicity. In this context, an increasing consensus claims the integration of microfluidic technologies within 3D cell culture, as the physical characterization of tumor spheroids is unavoidably demanded to standardize protocols and assays for in vitro testing. In this paper, we employed a flow-based method specifically conceived to measure weight, size and focused onto mass density values of tumor spheroids. These measurements are combined with confocal and digital imaging of such samples. We tested the spheroids of four colorectal cancer (CRC) cell lines that exhibit statistically relevant differences in their physical characteristics, even though starting from the same cell seeding density. These variations are seemingly cell line-dependent and associated with the number of growing cells and the degree of spheroid compaction as well, supported by different adenosine-triphosphate contents. We also showed that this technology can estimate the NK cell killing efficacy by measuring the weight loss and diameter shrinkage of tumor spheroids, alongside with the commonly used cell viability in vitro test. As the activity of NK cells relies on their infiltration rate, the in vitro sensitivity of CRC spheroids proved to be exposure time- and cell line-dependent with direct correlation to the cell viability reduction. All these functional aspects can be measured by the system and are documented by digital image analysis. In conclusion, this flow-based method potentially paves the way towards standardization of 3D cell cultures and its early adoption in cancer research to test antitumor immune response and set up new immunotherapy strategies.

Cross-Border Electricity Trading in Southeast Europe Towards an Internal European Market

The European Commission’s Target Model’s main objective is to integrate European electricity markets, leading to a single internal energy market and guaranteeing the instantaneous balance between electricity generation and demand. According to the target model for electricity trading, proposed by the European Network Transmission System Operators for Electricity (ENTSO-E), within each zone, electricity can be traded freely without taking into consideration network limitations. In contrast, for cross-border trading, the exchanges with other market areas are taken into account. Cross-border trade poses a further burden on the interconnection lines, resulting in increasing network congestion, which in turn restricts electricity trading. Thus, calculating the available capacity for trade has a significant ramification on the market. Today, the Available Transfer Capacity (ATC) mechanism dominates cross-border trading, but this methodology may be replaced by the Flow-Based (FB) approach across Europe. This paper investigates both approaches regarding the cross-border congestion management under the market coupling procedure. In our case study, the Southeast Europe (SEE) region is taken into consideration; it consists of both the FB and ATC approach in a five country (Greece, North Macedonia, Bulgaria, Serbia, and Romania) scenario. The purpose of our tests is to perform, compare, and evaluate the effectiveness of each method for the SEE region, while the main findings are the maximization of social welfare, better cross-border trading opportunities, and price convergence via the FB method.