scholarly journals The self-referencing oxygen-selective microelectrode: detection of transmembrane oxygen flux from single cells

1999 ◽  
Vol 202 (2) ◽  
pp. 211-218
Author(s):  
S.C. Land ◽  
D.M. Porterfield ◽  
R.H. Sanger ◽  
P.J. Smith
Keyword(s):  
Real Time ◽  
Single Cells ◽  
Light Response ◽  
The Self ◽  
Oxygen Flux ◽  
Metabolic Substrates ◽  
Translational Movement ◽  
Isolated Neuron ◽  
Time Changes ◽  
High Level

A self-referencing, polarographic, oxygen-selective microelectrode was developed for measuring oxygen fluxes from single cells. This technique is based on the translational movement of the microelectrode at a known frequency through an oxygen gradient, between known points. The differential current of the electrode was converted into a directional measurement of flux using the Fick equation. Operational characteristics of the technique were determined using artificial gradients. Calculated oxygen flux values matched theoretical values derived from static measurements. A test preparation, an isolated neuron, yielded an oxygen flux of 11.46+/−1.43 pmol cm-2 s-1 (mean +/− s.e.m.), a value in agreement with those available in the literature for single cells. Microinjection of metabolic substrates or a metabolic uncoupler increased oxygen flux, whereas microinjection of KCN decreased oxygen flux. In the filamentous alga Spirogyra greveilina, the probe could easily differentiate a 16.6% difference in oxygen flux with respect to the position of the spiral chloroplast (13.3+/−0.4 pmol cm-2 s-1 at the chloroplast and 11.4+/−0.4 pmol cm-2 s-1 between chloroplasts), despite the fact that these positions averaged only 10.6+/−1.8 microm apart (means +/− s.e.m.). A light response experiment showed real-time changes in measured oxygen flux correlated with changes in lighting. Taken together, these results show that the self-referencing oxygen microelectrode technique can be used to detect local oxygen fluxes with a high level of sensitivity and spatial resolution in real time. The oxygen fluxes detected reliably correlated with the metabolic state of the cell.

scholarly journals Graph-Based Construction of 3D Korean Giwa House Models

Buildings ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 68
Author(s):  
Mankyu Sung
Keyword(s):  
Data Structure ◽  
Computer Graphics ◽  
Real Time ◽  
Texture Image ◽  
Time Rate ◽  
Commercial Software ◽  
Spline Curve ◽  
High Level ◽  
Complicated Part ◽  
Different Parts

This paper proposes a graph-based algorithm for constructing 3D Korean traditional houses automatically using a computer graphics technique. In particular, we target designing the most popular traditional house type, a giwa house, whose roof is covered with a set of Korean traditional roof tiles called giwa. In our approach, we divided the whole design processes into two different parts. At a high level, we propose a special data structure called ‘modeling graphs’. A modeling graph consists of a set of nodes and edges. A node represents a particular component of the house and an edge represents the connection between two components with all associated parameters, including an offset vector between components. Users can easily add/ delete nodes and make them connect by an edge through a few mouse clicks. Once a modeling graph is built, then it is interpreted and rendered on a component-by-component basis by traversing nodes in a procedural way. At a low level, we came up with all the required parameters for constructing the components. Among all the components, the most beautiful but complicated part is the gently curved roof structures. In order to represent the sophisticated roof style, we introduce a spline curve-based modeling technique that is able to create curvy silhouettes of three different roof styles. In this process, rather than just applying a simple texture image onto the roof, which is widely used in commercial software, we actually laid out 3D giwa tiles on the roof seamlessly, which generated more realistic looks. Through many experiments, we verified that the proposed algorithm can model and render the giwa house at a real time rate.

scholarly journals Real-Time High-Level Acute Pain Detection Using a Smartphone and a Wrist-Worn Electrodermal Activity Sensor

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3956
Author(s):  
Youngsun Kong ◽  
Hugo F. Posada-Quintero ◽  
Ki H. Chon
Keyword(s):  
Real Time ◽  
Electrodermal Activity ◽  
Smartphone Application ◽  
Real Time Processing ◽  
Pain Stimulation ◽  
Significant Difference ◽  
Before And After ◽  
Electrical Pulses ◽  
Pain Detection ◽  
High Level

The subjectiveness of pain can lead to inaccurate prescribing of pain medication, which can exacerbate drug addiction and overdose. Given that pain is often experienced in patients’ homes, there is an urgent need for ambulatory devices that can quantify pain in real-time. We implemented three time- and frequency-domain electrodermal activity (EDA) indices in our smartphone application that collects EDA signals using a wrist-worn device. We then evaluated our computational algorithms using thermal grill data from ten subjects. The thermal grill delivered a level of pain that was calibrated for each subject to be 8 out of 10 on a visual analog scale (VAS). Furthermore, we simulated the real-time processing of the smartphone application using a dataset pre-collected from another group of fifteen subjects who underwent pain stimulation using electrical pulses, which elicited a VAS pain score level 7 out of 10. All EDA features showed significant difference between painless and pain segments, termed for the 5-s segments before and after each pain stimulus. Random forest showed the highest accuracy in detecting pain, 81.5%, with 78.9% sensitivity and 84.2% specificity with leave-one-subject-out cross-validation approach. Our results show the potential of a smartphone application to provide near real-time objective pain detection.

scholarly journals A Modified KNN Algorithm for High-Performance Computing on FPGA of Real-Time m-QAM Demodulators

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 627
Author(s):  
David Marquez-Viloria ◽  
Luis Castano-Londono ◽  
Neil Guerrero-Gonzalez
Keyword(s):  
Real Time ◽  
High Performance ◽  
Interference Mitigation ◽  
Parallel Implementation ◽  
Computational Time ◽  
Successful Implementation ◽  
Interchannel Interference ◽  
The Difference ◽  
High Level ◽  
Performance Computing

A methodology for scalable and concurrent real-time implementation of highly recurrent algorithms is presented and experimentally validated using the AWS-FPGA. This paper presents a parallel implementation of a KNN algorithm focused on the m-QAM demodulators using high-level synthesis for fast prototyping, parameterization, and scalability of the design. The proposed design shows the successful implementation of the KNN algorithm for interchannel interference mitigation in a 3 × 16 Gbaud 16-QAM Nyquist WDM system. Additionally, we present a modified version of the KNN algorithm in which comparisons among data symbols are reduced by identifying the closest neighbor using the rule of the 8-connected clusters used for image processing. Real-time implementation of the modified KNN on a Xilinx Virtex UltraScale+ VU9P AWS-FPGA board was compared with the results obtained in previous work using the same data from the same experimental setup but offline DSP using Matlab. The results show that the difference is negligible below FEC limit. Additionally, the modified KNN shows a reduction of operations from 43 percent to 75 percent, depending on the symbol’s position in the constellation, achieving a reduction 47.25% reduction in total computational time for 100 K input symbols processed on 20 parallel cores compared to the KNN algorithm.

scholarly journals Deep Reinforcement Learning for End-to-End Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2534
Author(s):  
Oualid Doukhi ◽  
Deok-Jin Lee
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Autonomous Navigation ◽  
Control Technique ◽  
Local Motion ◽  
Aerial Robots ◽  
Novel Approach ◽  
Outdoor Environments ◽  
Aerial Vehicle ◽  
High Level

Autonomous navigation and collision avoidance missions represent a significant challenge for robotics systems as they generally operate in dynamic environments that require a high level of autonomy and flexible decision-making capabilities. This challenge becomes more applicable in micro aerial vehicles (MAVs) due to their limited size and computational power. This paper presents a novel approach for enabling a micro aerial vehicle system equipped with a laser range finder to autonomously navigate among obstacles and achieve a user-specified goal location in a GPS-denied environment, without the need for mapping or path planning. The proposed system uses an actor–critic-based reinforcement learning technique to train the aerial robot in a Gazebo simulator to perform a point-goal navigation task by directly mapping the noisy MAV’s state and laser scan measurements to continuous motion control. The obtained policy can perform collision-free flight in the real world while being trained entirely on a 3D simulator. Intensive simulations and real-time experiments were conducted and compared with a nonlinear model predictive control technique to show the generalization capabilities to new unseen environments, and robustness against localization noise. The obtained results demonstrate our system’s effectiveness in flying safely and reaching the desired points by planning smooth forward linear velocity and heading rates.

scholarly journals Ferro-self-assembly: magnetic and electrochemical adaptation of a multiresponsive zwitterionic metalloamphiphile showing a shape-hysteresis effect

2021 ◽  
Vol 12 (1) ◽  
pp. 270-281
Author(s):  
Stefan Bitter ◽  
Moritz Schlötter ◽  
Markus Schilling ◽  
Marina Krumova ◽  
Sebastian Polarz ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Light Scattering ◽  
Dynamic Light Scattering ◽  
Real Time ◽  
Self Assembly ◽  
Hysteresis Effect ◽  
The Self ◽  
Self Organization ◽  
Stimuli Responsive ◽  
Optical Birefringence

The self-organization properties of a stimuli responsive amphiphile can be altered by subjecting the paramagnetic oxidized form to a magnetic field of 0.8 T and monitored in real time by coupling optical birefringence with dynamic light scattering.

scholarly journals The Relationship between Symptom Flare of Atopic Dermatitis and Airborne Japanese Cedar and Cypress Pollen Counts: A Self-Scoring Diary Study

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Haruko Nishie ◽  
Mariko Kato ◽  
Shiori Kato ◽  
Hiroshi Odajima ◽  
Rumiko Shibata ◽  
...  
Keyword(s):  
Atopic Dermatitis ◽  
Real Time ◽  
Pollen Season ◽  
Airborne Pollen ◽  
Japanese Cedar ◽  
Diary Study ◽  
Pollen Counts ◽  
High Level ◽  
The Relationship

Background. With an increase in Japanese cedar and cypress (JC) pollinosis, the relationship between JC pollen and atopic dermatitis (AD) has been studied. Some reports suggest that JC pollen can be one exacerbating factor for AD, but there has been no report that discusses JC pollen counts relating to AD symptom flare although actual airborne JC pollen counts can widely fluctuate throughout the pollen season. Objective. The relationship between symptom flare of AD and airborne JC pollen counts was examined. Methods. We monitored JC pollen counts in real time and divided the counts into low and high level. We then analyzed self-scored “itch intensity” recorded by 14 AD patients through a self-scoring diary. Results. Among the 14 patients, 7 had significantly higher itch intensity while the pollen counts were high. Conclusion. Even during the pollen season, actual airborne pollen counts can widely fluctuate. Our study suggested that symptom flare of AD could be influenced by the actual pollen counts.

scholarly journals Equity Effects of Congestion Charges: An Exploratory Analysis with MATSim

2017 ◽  
Vol 2670 (1) ◽  
pp. 75-82 ◽  
Author(s):  
Lucas Meyer de Freitas ◽  
Oliver Schuemperlin ◽  
Milos Balac ◽  
Francesco Ciari
Keyword(s):  
Travel Time ◽  
Large Scale ◽  
Agent Based ◽  
Promising Tool ◽  
Travel Time Savings ◽  
Time Savings ◽  
Time Changes ◽  
High Level ◽  
Congestion Charging ◽  
Equity Effects

This paper shows an application of the multiagent, activity-based transport simulation MATSim to evaluate equity effects of a congestion charging scheme. A cordon pricing scheme was set up for a scenario of the city of Zurich, Switzerland, to conduct such an analysis. Equity is one of the most important barriers toward the implementation of a congestion charging system. After the challenges posed by equity evaluations are examined, it is shown that agent-based simulations with heterogeneous values of time allow for an increased level of detail in such evaluations. Such detail is achieved through a high level of disaggregation and with a 24-h simulation period. An important difference from traditional large-scale models is the low degree of correlation between travel time savings and welfare change. While traditional equity analysis is based on travel time savings, MATSim shows that choice dimensions not included in traditional models, such as departure time changes, can also play an important role in equity effects. The analysis of the results in light of evidence from the literature shows that agent-based models are a promising tool to conduct more complete equity evaluations not only of congestion charges but also of transport policies in general.

Self-referencing optrodes for measuring spatially resolved, real-time metabolic oxygen flux in plant systems

Planta ◽  
2010 ◽  
Vol 232 (5) ◽  
pp. 1087-1099 ◽  
Author(s):  
Eric S. McLamore ◽  
David Jaroch ◽  
M. Rameez Chatni ◽  
D. Marshall Porterfield
Keyword(s):  
Real Time ◽  
Oxygen Flux ◽  
Spatially Resolved

scholarly journals Deep-Framework: A Distributed, Scalable, and Edge-Oriented Framework for Real-Time Analysis of Video Streams

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4045
Author(s):  
Alessandro Sassu ◽  
Jose Francisco Saenz-Cogollo ◽  
Maurizio Agelli
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Video Data ◽  
Video Analytics ◽  
Web Based ◽  
Real Time Analysis ◽  
Open Source Framework ◽  
Cluster Configuration ◽  
Time Requirements ◽  
High Level

Edge computing is the best approach for meeting the exponential demand and the real-time requirements of many video analytics applications. Since most of the recent advances regarding the extraction of information from images and video rely on computation heavy deep learning algorithms, there is a growing need for solutions that allow the deployment and use of new models on scalable and flexible edge architectures. In this work, we present Deep-Framework, a novel open source framework for developing edge-oriented real-time video analytics applications based on deep learning. Deep-Framework has a scalable multi-stream architecture based on Docker and abstracts away from the user the complexity of cluster configuration, orchestration of services, and GPU resources allocation. It provides Python interfaces for integrating deep learning models developed with the most popular frameworks and also provides high-level APIs based on standard HTTP and WebRTC interfaces for consuming the extracted video data on clients running on browsers or any other web-based platform.

Sign in / Sign up

Export Citation Format

Share Document