Multiple Capture Research Articles

Spatial barcoding-enabled highly multiplexed immunoassay with digital microfluidics

Digital microfluidics (DMF), facilitating independent manipulation of microliter samples, provides an ideal platform for immunoassay detection; however, suffering limited multiplexity. To address the need, herein we described a digital microfluidics (DMF) platform that realizes spatial barcoding on the Teflon-coated indium tin oxide (ITO) glass side to fulfill highly multiplexed immunoassay (10+) with low-volume samples (∼4 μL) in parallel, representing the highest multiplexing recorded to date for DMF-actuated immunoassay. Planar-based spatial immobilization of multiple capture antibodies was realized on a Teflon-coated ITO glass side, which was then used as the top plate of the DMF device. Droplets containing analytes, secondary antibodies, and fluorescent signaling reporters with low volume, which were electrically manipulated by our DMF control system, were shuttled sequentially along the working electrodes to complete the immuno-reaction. Evaluation of platform performance with recombinant proteins showed excellent sensitivity and reproducibility. To test the feasibility of our platform in analyzing multiplex biomarkers of the immune response, we used lipopolysaccharide-stimulated macrophages as a model system for protein secretion dynamics studies. As a result, temporal profiling of pro-inflammatory cytokine secretion dynamics was obtained. The spatial barcoding strategy presented here is easy-to-operate to enable a more comprehensive evaluation of protein abundance from biological samples, paving the way for new opportunities to realize multiplexity-associated applications with the DMF platform.

Deformable Graph Convolutional Networks

Graph neural networks (GNNs) have significantly improved the representation power for graph-structured data. Despite of the recent success of GNNs, the graph convolution in most GNNs have two limitations. Since the graph convolution is performed in a small local neighborhood on the input graph, it is inherently incapable to capture long-range dependencies between distance nodes. In addition, when a node has neighbors that belong to different classes, i.e., heterophily, the aggregated messages from them often negatively affect representation learning. To address the two common problems of graph convolution, in this paper, we propose Deformable Graph Convolutional Networks (Deformable GCNs) that adaptively perform convolution in multiple latent spaces and capture short/long-range dependencies between nodes. Separated from node representations (features), our framework simultaneously learns the node positional embeddings (coordinates) to determine the relations between nodes in an end-to-end fashion. Depending on node position, the convolution kernels are deformed by deformation vectors and apply different transformations to its neighbor nodes. Our extensive experiments demonstrate that Deformable GCNs flexibly handles the heterophily and achieve the best performance in node classification tasks on six heterophilic graph datasets. Our code is publicly available at https://github.com/mlvlab/DeformableGCN.

Design of an Integrated Platform for Active Debris Removal

In research concerning active debris removal, scholars have proposed dozens of schemes for removing debris. However, every scheme has both advantages and disadvantages, and no scheme possesses an overwhelming advantage. This paper proposes an integrated platform scheme which integrates multiple capture and deorbit technologies, such as a tethered net, harpoon, and robotic arm, to improve the success rate in terms of the active removal of debris of different shapes and different sizes. The design of the mechanisms of the integrated platform is presented in detail.

Developing Techniques for Rigging and Motion Capture to Simplify 3D Animation

Our project focused on finding ways to simplify 3D animation by streamlining the rigging process and by using motion capture data. Rigging is a method of creating a “skeleton” for a 3D model to be manipulated and animated while motion capture uses recorded movements to animate a 3D character in movies and video games. Previous methods such as manual rigging and keyframe animation are time consuming and difficult for novice animators to learn. We sought a faster approach that would allow us to teach 3D animation to beginner students in a single semester. Using a more efficient rigging process and multiple motion capture sources, we have created an online library of motion-ready 3D character rigs and a variety of pre-captured animations for use. Our rigs can be animated by beginners in less than five minutes and were used to support the first course in 3D Animation at Florida Gulf Coast University.

A tripartite-enzyme via curcumin regarded as zymoexciter towards highly efficient relieving reperfusion injury

For alleviating ischemic reperfusion injury, reasonable design mimic multi-functional nanozyme can simultaneously capture ROS and inhibit inflammatory factors, which plays an important role. However, the low efficiency of natural enzyme and their ability to capture only a single species limit their effectiveness. Therefore, additional materials to capture other ROS are highly needed. These motivates us to construct a nanozyme via hybridize/coupled curcumin (CUR) with ZnCe Layered Rare-earth Hydroxide (ZnCe-LRH) to achieve highly efficient ROS scavenging efficiency and the multiple ROS capture (denoted as CUR/ZnCe-LRH). Ce element was highly dispersed on the LRH layer, and CUR further coordinated with Zn on the layer to form a stable nanozyme structure. This mimic tripartite nanozyme can not only simulate superoxide dismutase (SOD) and catalase (CAT) activity to capture •O2− and H2O2, but also arrest •OH within a short period of time, which can be regarded as the tripartite nanozyme. Density functional theory (DFT) calculations can further confirm the high efficient ROS scavenging mechanism by the CUR/ZnCe-LRH systems. In vivo results can further probe that this CUR/ZnCe-LRH can also suppress inflammation- and immune response–induced injury, thus achieving good prevention and treatment in neuroprotective therapy. The infarct area can reduce by 78% after the reperfusion therapy and the neurological deficit score can reduce from 3.50 to 0.67. This strategy provided a novel multifunctional enzyme mimetic for ischemia–reperfusion therapy and clarifies the application mechanism of neuroprotection against ischemia–reperfusion injury.

Nitrogen-doped porous carbons from polyacrylonitrile fiber as effective CO2 adsorbents

In this report, nitrogen-doped porous carbons were synthesized from polyacrylonitrile fiber by a facile two-step synthesis process i.e. carbonization followed by KOH activation. Activation temperature and KOH/carbon ratio are two parameters to tune the porosity and surface chemical properties of sorbents. The as-obtained sorbents were carefully characterized. Special attention was paid concerning the change of sorbents’ morphology with respect to synthesis conditions. Under the activation temperatures of this study, the sorbents can still retain their fibrous structure when the KOH/carbon mass ratio is 1. Further increasing the KOH amount will destroy the original morphology of polyacrylonitrile fiber. CO2 adsorption performance tests show that a sorbent retaining the fibrous shape possesses the highest CO2 uptake of 3.95 mmol/g at 25°C and 1 bar. Comprehensive investigation found that the mutual effect of narrow microporosity and doped N content govern the CO2 adsorption capacity of these adsorbents. Furthermore, these polyacrylonitrile fiber-derived carbons present multiple outstanding CO2 capture properties such as excellent recyclability, high CO2/N2 selectivity, fast adsorption kinetics, suitable heat of adsorption, and good dynamic adsorption capacity. Hence, nitrogen-doped porous carbons with fibrous structure are promising in CO2 capture.

Using ensemble methods to improve the robustness of deep learning for image classification in marine environments

Abstract Deep learning has been shown to be effective for classification of coral in benthic imagery, and is becoming a tool for use in many monitoring programs around the world. Although deep learning accuracy for coral reef classification has been well published for studies where validation metrics are generated from data within surveys, little research has been done on the transferability and generalisability of deep learned models to data never seen by the trained model. Examples include data across multiple capture methods, camera systems, habitat types, water quality conditions and temporal studies. In this paper we investigate the use of deep ensembling to measure the reliability of predictions in new or unseen environments. In this paper we show that ensemble methods are more stable in their calibration across dataset shifts compared with other approaches. Ensembles show more robust uncertainty quantification in unseen environments compared to alternative methods, thus providing more confidence in the use of pre‐trained models in unconstrained environments. These results show that ensembles should be the de facto standard for any practitioner using deep learning for benthic image automation, and applying deep learning approaches to coral classification.

Techno-Economic Analysis of Amine-based CO2 Capture Technology: Hunter Plant Case Study

The technical and commercial feasibility of carbon dioxide (CO2) capture with sequestration (CCS) in a geologic formation adjacent to PacifiCorp's Hunter Plant was evaluated. This includes the development of expected performance, and capital and operating costs associated with implementing CCS on Unit 3 at the Hunter Plant that burns low-sulfur, sub-bituminous coal. This study effort also includes the evaluation of multiple capture levels using a commercially available amine-based system as the basis for the capture technology. The system design and costs were developed based on the Mitsubishi Heavy Industries' (MHI) KM-CR Process® with KS-1™ solvent. Due to economies of scale, the overall cost of capture ($/ton of CO2 removed) is less at larger capture rates. The cost of capture ranges from $50, $61, $74/ton CO2 removed for 90%, 65% and 1000 lbs/MWh,g of CO2 capture from Hunter 3 with the CO2 purity greater than 95%.

Дисперсионный транспорт дырочных поляронов в МОП-структурах после ионизирующего излучения

t is shown that the description of the dispersive transport of hole polarons based on the multiple capture model makes it possible to quantitatively describe the kinetics of the accumulation and relaxation of space charge in MOS- structures after ionizing irradiation at low temperatures. Modeling of time dependences of threshold voltage on temperature, electric field strength and gate oxide thickness is carried out. It is shown that the kinetics of space charge relaxation is determined by the hopping transport of hole polarons with the levels of localized states in the range of 0.08−0.55 eV, the concentration of polaron states, the influence of the electric field strength on the average polaron energy, as well as gate oxide thickness on dispersive parameter. The polaron radius is estimated.

Dispersive transport of Hole polarons in MOS-structures after the ionizing irradiation

It is shown that the description of the dispersive transport of hole polarons based on the multiple capture model makes it possible to quantitatively describe the kinetics of the accumulation and relaxation of space charge in MOS-structures after ionizing irradiation at low temperatures (80-293 K). Modeling of time dependences of threshold voltage on temperature, electric field strength and gate oxide thickness is carried out. It is shown that the kinetics of space charge relaxation is determined by the hopping transport of hole polarons with the levels of localized states in the range of 0.08-0.55 eV, the concentration of polaron states, the influence of the electric field strength on the average polaron energy, as well as gate oxide thickness on dispersive parameter. The polaron radius is estimated. Keywords: MOS-structure, the ionizing radiation, dispersive transport, polarons, modeling.

Creating space and time for innovation - a methodology for building adaptation design appraisal using physics-based simulation tools and interactive multi-objective optimization

PurposeIt is crucial to consider the multitude of possible building adaptation design strategies for improving the existing conditions of building stock as an alternative to demolition.Design/methodology/approachIntegration of physics-based simulation tools and decision-making tools such as Multi-Attribute Utility (MAU) and Interactive Multi-objective Optimization (IMO) in the design process enable optimized design decision-making for high-performing buildings. A methodology is presented for improving building adaptation design decision making, specifically in the early-stage design feasibility analysis. Ten residential building adaptation strategies are selected and applied to one primary building system for eight performance metrics using physics-based simulation tools. These measures include energy use, thermal comfort, daylighting, natural ventilation, systems performance, life cycle, cost-benefit and constructability. The results are processed using MAU and IMO analysis and are validated through sensitivity analysis by testing one design strategy on three building systems.FindingsQuantifiable comparison of building adaptation strategies based on multiple metrics derived from physics-based simulations can assist in the evaluation of overall environmental performance and economic feasibility for building adaptation projects.Research limitations/implicationsThe current methodology presented is limited to the analysis of one decision-maker at a time. It can be improved to include multiple decision-makers and capture varying perspectives to reflect common practices in the industry.Practical implicationsThe methodology presented supports affordable generation and analysis of a large number of design options for early-stage design optimization.Originality/valueGiven the practical implications, more space and time is created for exploration and innovation, resulting in potential for improved benefits.

The state of Australian performance design: A roundtable discussion on scenographic practice, education and research through the lens of the Prague Quadrennial

As the Prague Quadrennial of Performance Design and Space 2019 (PQ19) drew to a close, Australian designers, researchers and educators gathered to discuss the impact of PQ on our scenographic communities while querying the evolutions and challenges facing design practice. Australia’s vast geography made this event a unique opportunity to bring together leading experts from multiple states and capture contemporary perspectives. At the midpoint between the 2019 and 2023 gatherings – a time of global pandemics, political unrest and educational transformation – this article offers the outcomes of this roundtable as a unique snapshot of the state of design practice within Australia through the lens of the Quadrennial. The roundtable was themed around Australia’s presence at PQ19, the effects of PQ19 on those present and the ripples to be felt by those at home, and what attendance illuminated about current developments and concerns in practice, teaching and research. Led by practitioner-researchers Tessa Rixon and Madeline Taylor, the roundtable featured both the curators of Australia’s country and student exhibits; award-winning set, costume and lighting designers with diverse experiences from national opera to independent theatre; and educators and researchers from the nation’s top universities. The resulting discussion presents a unique perspective on the gaps and weaknesses in the design education, practice and research; first-hand insights on the challenges and opportunities available in both exhibiting and participating in the PQ; and the need to actively promote and privilege diverse voices and a multiplicity of representations in the process of claiming a ‘national’ scenographic identity. The roundtable was the first to capture multiple expert first-person Australian perspectives on the PQ while simultaneously contributing to the ongoing international discussion of performance design through the lens of artists, educators and researchers.

Smartphone Enabled Point-of-Care Detection of Serum Biomarkers.

Sandwich immunoassays are the gold standard for detection of protein analytes. Here, we describe an ultrasensitive point-of-care sandwich immunoassay platform for the detection of biomarkers directly from blood or serum using a custom-built smartphone detector. Testing undiluted blood or serum is challenging due to the complexity of the matrix. Proteins nonspecifically adsorb to and cells often adhere to the assay surface, which can drastically impact the analytical sensitivity of the assay. To address this problem, our assay is built upon a "nonfouling" polymer brush "grafted from" a glass slide, which eliminates nearly all nonspecific binding and therefore increases the signal-to-noise ratio and greatly improves the analytical performance of the test. The two components required to perform a sandwich immunoassay are inkjet-printed directly onto the surface: (1) "stable" capture antibodies that remain entrapped in the brush even after exposure to a liquid sample and (2) fluorescently labeled "soluble" detection antibodies that dissolve upon exposure to a liquid sample. The polymer brush provides hydration to the antibodies, allowing them to remain stable and active over prolonged periods of time. When a liquid sample containing a biomarker of interest is dispensed onto the chip, the detection antibodies dissolve and diffuse to the stable capture spots forming a complex that sandwiches the analyte and that has a fluorescence intensity proportional to the concentration of the biomarker in solution, which can be measured using a custom-built smartphone detector. As multiple capture antibodies can be printed as discrete capture spots, the assay can be easily multiplexed without the need for multiple fluorophores. This chip and detector platform can be utilized for the point-of-care detection of low-abundance biomarkers directly from blood or serum in low-resource settings.

Consequences of simulated multiple catch-and-release events and different handling procedures on reflex impairment, ventilation rate, and body condition in Tor khudree

As catch-and-release becomes more popular and angling pressure increases, it is likely that fish in popular fisheries will experience catch-and-release events on more than one occasion (i.e., “multiple captures”). Anecdotal reports from anglers suggest that blue-finned mahseer (Tor khudree) in WASI Lake, Karnataka, India, commonly experience multiple capture events that are closely timed together (e.g., often on successive days). To determine whether multiple capture events were likely to result in cumulative physiological effects compared to single capture events, we quickly angled (i.e., landed in < 2.5 min) 124 blue-finned mahseer and placed them in one of four simulated capture treatment groups: control, air exposure, chase, or a combination of air exposure and chase. Blue-finned mahseer were held overnight in a net pen and subjected to a second (n = 91) or third (n = 60) instance of simulated capture. Our results showed increasing ventilation rates and condition score but no pattern in reflex impairment score in blue-finned mahseer for each treatment group and across each day. Ventilation rates were lowest in the air exposure and combination treatments than for other treatment groups, possibly indicating a masking effect from air exposure. The findings of our study indicate blue-finned mahseer are relatively robust to capture-related stressors, even when experienced with short intervals between fisheries encounters; however, we urge further research for improved understanding of the manner in which these stressors interact, particularly in tropical, freshwater environments.

Microfluidic technology for multiple single-cell capture.

Microfluidic devices are widely used in single-cell capture and for pairing single cells or groups of cells for cell-cell interaction analysis; these advances have improved drug screening and cell signal transduction analysis. The complex in vivo environment involves interactions between two cells and among multiple cells of the same or different phenotypes. This study reviewed the core principles and performance of several microfluidic multiple- and single-cell capture methods, namely, the microwell, valve, trap, and droplet methods. The advantages and disadvantages of the methods were compared, and suggestions regarding their application to multiple-cell capture were provided. The results may serve as a reference for research on microfluidic multiple single-cell coculture technology.

Capacitive Removal of Fluoride Ions via Creating Multiple Capture Sites in a Modulatory Heterostructure

Fluoride pollution has become a major concern because of its adverse effects on human health. However, the removal capacity of defluorination agents in traditional methods is far from satisfactory. Herein, capacitive removal of F- ions via creating multiple capture sites in a modulatory heterostructure has been originally demonstrated. The heterostructure of uniformly dispersed Al2O3 coating on hollow porous nitrogen-doped carbon frameworks was precisely synthesized by atomic layer deposition. An exceptional F- ion removal efficiency at 1.2 V (95.8 and 92.9% in 5 and 10 mg/L F- solutions, respectively) could be finally achieved, with a good regeneration ability after 20 consecutive defluorination cycles. Furthermore, we investigated the removal mechanisms of F- ions by in situ Raman, in situ X-ray diffraction, and ex situ X-ray photoelectron spectroscopy measurements. The promotional removal capacity was realized by the multiple capture sites of the reversible conversion of Al-F species and the insertion of F- ions into the carbon skeleton. This work offers an important new pathway and deep understanding for efficient removal of F- ions from wastewater.

Capture of CO2 and Water While Driving for Use in the Food and Agricultural Systems

This white paper proposes research on the design and evaluation of an integrated system assembled to the vehicle with no energy penalty where a sequence of processes, cooling, heating, mass transfer, and compression, will take place while driving. The increasing demand for fresh produce has led to an expansion of the US urban agriculture industry (greenhouses) which uses carbon dioxide (CO2) enrichment from burning fossil fuels to increase plant productivity and to shorten the plant growth time. The demand for CO2 and water in greenhouses is massive (2.81 kg CO2eq/kg produce, 22 L water/kg produce), and alternate CO2 and water delivery sources are essential to make post-harvest food processing technologies such as dense-phase CO2 pasteurization of beverages more sustainable. Internal combustion engines (ICE) have an average efficiency of about 30%, with 30% of the thermal energy wasted in the exhaust gases. A typical passenger vehicle emits about 4.6 metric tons of CO2 and 21,000 l of water per year into the environment. Although multiple carbon capture technologies exist, the size of these plants is large, their unit operations are fixed, and the use of novel materials is limited. In this white paper, we propose to retrofit the wasted energy in a car’s exhaust to capture, concentrate, store, and deliver liquid CO2 and water for agricultural and food systems. Preliminary thermodynamic and exergy analysis indicates that this is feasible. Specially designed heat and mass transfer units with novel materials and 3D printing technology could be easily deployed and used while driving to mitigate the global warming problem while addressing the needs of agricultural systems.

Mosquitoes Know No Borders: Surveillance of Potential Introduction of Aedes Species in Southern Québec, Canada.

Current climatic conditions limit the distribution of Aedes (Stegomyia) albopictus (Skuse, Diptera: Culicidae) in the north, but predictive climate models suggest this species could establish itself in southern Canada by 2040. A vector of chikungunya, dengue, yellow fever, Zika and West Nile viruses, the Ae. Albopictus has been detected in Windsor, Ontario since 2016. Given the potential public health implications, and knowing that Aedes spp. can easily be introduced by ground transportation, this study aimed to determine if specimens could be detected, using an adequate methodology, in southern Québec. Mosquitoes were sampled in 2016 and 2017 along the main roads connecting Canada and the U.S., using Biogent traps (Sentinel-2, Gravide Aedes traps) and ovitraps. Overall, 24 mosquito spp. were captured, excluding Ae. Albopictus, but detecting one Aedes (Stegomyia) aegypti (Skuse) specimen (laid eggs). The most frequent species among captured adults were Ochlerotatus triseriatus, Culex pipiens complex, and Ochlerotatus japonicus (31.0%, 26.0%, and 17.3%, respectively). The present study adds to the increasing number of studies reporting on the range expansions of these mosquito species, and suggests that ongoing monitoring, using multiple capture techniques targeting a wide range of species, may provide useful information to public health with respect to the growing risk of emerging mosquito-borne diseases in southern Canada.

Matrix Resolving Function in the Nonstationary Linear Group Pursuit Problem Concepting Multiple Capture

In finite-dimensional Euclidean space, an analysis is made of the problem of pursuit of a single evader by a group of pursuers, which is described by a system of the form [Formula: see text] The goal of the group of pursuers is the capture of the evader by no less than [Formula: see text] different pursuers (the instants of capture may or may not coincide). Matrix resolving functions, which are a generalization of scalar resolving functions, are used as a mathematical basis of this study. Sufficient conditions are obtained for multiple capture of a single evader in the class of quasi-strategies. Examples illustrating the results obtained are given.

Integration of a fiber-based cell culture and biosensing system for monitoring of multiple protein markers secreted from stem cells

We propose a new platform that can integrate three-dimensional cell culture scaffold and a surface-enhanced Raman spectroscopy (SERS)-based biosensor by stacking them to form a multilayer system, which would allow monitoring of the protein markers secreted from cultured stem cells without periodic cell and/or media collection. The cell culture scaffold supported the proliferation and osteogenic differentiation of adipose-derived mesenchymal stem cells (ADSCs). The SERS capture substrate detected protein markers in combination with SERS tag made with Au–Ag alloy nanoboxes. Incorporating the different Raman reporters into the SERS tag allowed easy identification of target proteins for multiplex assays. The resultant SERS-based immunoassay could detect the pg/mL levels of protein markers without crosstalk and interference. When one ADSC culture scaffold and multiple SERS capture substrates were integrated and incubated in differentiation culture media, our system was sufficiently sensitive to monitor time-dependent secretion of three different osteogenic protein markers from ADSCs during their osteogenic differentiation. Since the sensor and cell culture scaffold can be manipulated independently, various cell and biomarker combinations are possible to obtain relevant information regarding the actual state of the different types of cells.