Actual Probe Research Articles

Action Planning Renders Objects in Working Memory More Attentionally Salient.

A rapidly growing body of work suggests that visual working memory (VWM) is fundamentally action oriented. Consistent with this, we recently showed that attention is more strongly biased by VWM representations of objects when we plan to act on those objects in the future. Using EEG and eye tracking, here, we investigated neurophysiological correlates of the interactions between VWM and action. Participants (n = 36) memorized a shape for a subsequent VWM test. At test, a probe was presented along with a secondary object. In the action condition, participants gripped the actual probe if it matched the memorized shape, whereas in the control condition, they gripped the secondary object. Crucially, during the VWM delay, participants engaged in a visual selection task, in which they located a target as fast as possible. The memorized shape could either encircle the target (congruent trials) or a distractor (incongruent trials). Replicating previous findings, we found that eye gaze was biased toward the VWM-matching shape and, importantly, more so when the shape was directly associated with an action plan. Moreover, the ERP results revealed that during the selection task, future action-relevant VWM-matching shapes elicited (1) a stronger Ppc (posterior positivity contralateral), signaling greater attentional saliency; (2) an earlier PD (distractor positivity) component, suggesting faster suppression; (3) a larger inverse (i.e., positive) sustained posterior contralateral negativity in incongruent trials, consistent with stronger suppression of action-associated distractors; and (4) an enhanced response-locked positivity over left motor regions, possibly indicating enhanced inhibition of the response associated with the memorized item during the interim task. Overall, these results suggest that action planning renders objects in VWM more attentionally salient, supporting the notion of selection-for-action in working memory.

A Novel Ultrasound Imaging Assistance UI: Using Marker‐Based Coordinate System for Real‐Time Breathing Monitoring and Probe Positioning

Ultrasound is widely employed in medical examinations due to its noninvasive, radiation‐free, and convenient features. However, the quality of acquired ultrasound images is highly dependent on the skill of the operator and experience, which significantly limits the use of ultrasound. In this study, we propose a new user interface (UI) designed to assist novices in independently acquiring accurate ultrasound images. The operator can complete image acquisition by adjusting the position and angle of the actual probe to align the projected probe on the UI screen to a specific position, while simultaneously observing the breath state of the subject to capture ultrasound images at the appropriate position and moment. We compare our UI with a previous UI in an experiment. The results demonstrate that novice operators can acquire more accurate ultrasound images using our UI compared to the previous UI, indicating that our UI offers improved guidance. Regarding breath state observation, the experiment reveals a strong association between changes in lung air volume of a subject and respiratory level changes measured by our system. © 2024 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Nano-positive up negative down in binary oxide ferroelectrics

Ferroelectric HfO2 and ZrO2-based materials are promising candidates for next-generation ferroelectric devices, but their characterization is challenging due to complex factors such as crystal phases, degradation mechanisms, and local inhomogeneities. In this work, we propose a novel nanosized positive-up-negative-down (PUND) method to assess the ferroelectric response of doped-HfO2. This method is based on actual current probing and is immune to most electrostatic artifacts that plague other electrical atomic force microscopy (AFM) techniques. We demonstrate the PUND method’s ability to induce ferroelectric switching in Si-doped HfO2 and investigate the distinctive PUND response obtained for individual grains. We also extract the polarization charge based on a direct estimate of the tip–sample contact area. The proposed PUND method is a significant innovation as it is a method to combine the high spatial resolution of AFM with the immunity to electrostatic artifacts of current probing. This makes it a powerful tool for studying ferroelectric materials at the nanoscale, where local inhomogeneities and other effects can have a significant impact on their behavior. The PUND method is also notable for its ability to extract polarization charge based on a direct estimate of the tip–sample contact area. This is a significant improvement over previous methods, which often relied on indirect or approximate estimates of the contact area. Overall, the PUND method is a novel and innovative technique that offers significant advantages for the characterization of ferroelectric materials at the nanoscale. It is expected to have a major impact on the research and development of next-generation ferroelectric devices.

Vision-Based Target Tracking Controller Design for Asteroid Flyby Problem

An accurate target tracking system improves the quality of flyby imaging of the target and consequently aids effective planetary exploration. A vision-based tracking system is one of the more popular systems, utilizing imaging data to achieve the required tracking accuracy. However, recent high-accuracy target tracking requirements cannot be achieved with targeting error feedback only. This paper summarizes the asteroid flyby mission characteristics and requirements, shows how possible error sources in the tracking system, and displays an exemplar control system design. The tracking error source is generally divided into a navigation error, which is a tracking profile generation error, and a control error, which is caused by the control system. A high-quality onboard relative-trajectory determination system is required to improve the navigation accuracy of the control system, because the pre-designed or offline-estimated relative trajectory contains uncertainties that cause the tracking profile generation error. Previous studies focused on this navigation error because of its sensitive effect on control system performance, showing some methods for improvement. This paper discusses how the control system can be improved to achieve greater precision during target tracking by considering the navigation and system characteristics. A realistic case study scenario is defined and analyzed based on an actual target tracking interplanetary probe mission. The characteristics of the designed control system are presented and its performance is analyzed via numerical simulation, using the case study data.

Mimicking non-ideal instrument behavior for hologram processing using neural style translation.

Holographic cloud probes provide unprecedented information on cloud particle density, size and position. Each laser shot captures particles within a large volume, where images can be computationally refocused to determine particle size and location. However, processing these holograms with standard methods or machine learning (ML) models requires considerable computational resources, time and occasional human intervention. ML models are trained on simulated holograms obtained from the physical model of the probe since real holograms have no absolute truth labels. Using another processing method to produce labels would be subject to errors that the ML model would subsequently inherit. Models perform well on real holograms only when image corruption is performed on the simulated images during training, thereby mimicking non-ideal conditions in the actual probe. Optimizing image corruption requires a cumbersome manual labeling effort. Here we demonstrate the application of the neural style translation approach to the simulated holograms. With a pre-trained convolutional neural network, the simulated holograms are "stylized" to resemble the real ones obtained from the probe, while at the same time preserving the simulated image "content" (e.g. the particle locations and sizes). With an ML model trained to predict particle locations and shapes on the stylized data sets, we observed comparable performance on both simulated and real holograms, obviating the need to perform manual labeling. The described approach is not specific to holograms and could be applied in other domains for capturing noise and imperfections in observational instruments to make simulated data more like real world observations.

CFD-supported data reduction of hot-wire anemometry signals for compressible organic vapor flows

For obtaining turbulent fluctuations in compressible organic vapor flows, computational fluid dynamics (CFD) analysis tools were used to support the data reduction process of hot-wire anemometry signals. It was found that CFD can help during the calibration process of actual hot-wire probes operated in the constant-temperature mode. Such an approach is beneficial for determining the dependency of the sensitivity coefficients on Reynolds and Mach numbers. Due to the small Kolmogorov scales, corrections are needed for probes with finite wire lengths. The experimental and numerical analysis considering the decay of turbulence downstream a grid indicated that the correction scheme proposed by Wyngaard leads to consistent results for compressible organic vapors. The new developments provide recommendations for obtaining turbulent quantities of compressible organic vapor flows utilizing hot-wire anemometry.

Robust fault detection and diagnosis of primary air data sensors in the presence of atmospheric turbulence

Abstract This paper presents a fault detection and diagnosis (FDD) algorithm for various faults in the primary air data sensors (PADS) of an aircraft in the presence of external disturbances such as atmospheric turbulence. Rapid wind variations due to turbulence induce excessive error in the externally fitted air data probe measurements, which may lead to loss of control and misinterpretations by the flight crew. In adverse environmental conditions, the FDD of air data prefers robust and adaptive air data estimates that use an analytical redundancy approach with fewer computations. The proposed method considers the kinematics of the aircraft instead of the dynamics used in the state-of-the-art algorithms. The advantage of using kinematics is that it can reduce modeling errors significantly, avoiding high false alarm rates in the FDD process. For the estimation of stable and accurate air data under external disturbance, the inertial navigation system and global positioning system (INS/GPS) output are considered instead of actual air data probe or sensor measurements. The proposed algorithm uses estimates of air data using an exponentially weighted adaptive extended Kalman filter (EW-AEKF) to detect and diagnose PADS faults, which can perform well even in the presence of uncertain noise due to atmospheric turbulence experienced during flight. The simulation was carried out to validate the algorithm with flight data obtained from the X-Plane flight simulator under moderate atmospheric turbulence. The simulation experiments were carried out using the MATLAB programming platform. The results show that the proposed method achieves satisfactory FDD performance with lower root mean square error (RMSE) and computation time than traditional EKF-based algorithms.

Compensation for attenuation on ultrasonic testing at TF coil structure of ITER

The ITER Toroidal Field Coil (TFC) is a massive 16 m × 9 m “D”-shape-superconducting magnet composed of winding pack (WP) and TF coil structure (TFCS). The TFCS is made of thick austenitic stainless steel with over 100 mm. The ultrasonic testing (UT) is used to the welding examination. The longitudinal wave is selected since it is generally used for UT of austenitic stainless-steel welds. There is a concern about the attenuation of the signal level of UT, because the ultrasonic wave is scattered through the weld metal of austenitic stainless steel. This paper reports the following compensation method against the attenuation of the UT signal with actual data applied for ITER TFCS. In the ITER TFCS fabrication, the attenuation of the UT beam in the weld is compensated by the transfer correction factor obtained from a test piece made of the actual TFCS material and weld metal during calibration. UT is performed using distance amplitude characteristic (DAC) curve obtained with a calibration block made from the base material of TFCS with side drill holes (SDHs). In order to capture the sensitivity difference between base material and weld metal, signal obtained with a reference block made from welding joint of TFCS with the same SDHs in the weld are plotted on the DAC. The sensitivity difference is obtained by difference of signal level on DAC and the plot. Then, relationship between the sensitivity difference and distance propagating in the weld metal is obtained. The sensitivity difference is used for assessment of UT signal level to correct decreasing by weld metal selecting proper sensitivity difference with respect to distance propagating in the weld metal in actual UT. This paper includes test results obtained by manufacturing companies using the actual UT probes for TFCS fabrication. The paper also provides obtained correlation between propagation distance in the weld metal and sensitivity difference.

Neural network processing of holographic images

Abstract. HOLODEC, an airborne cloud particle imager, captures holographic images of a fixed volume of cloud to characterize the types and sizes of cloud particles, such as water droplets and ice crystals. Cloud particle properties include position, diameter, and shape. In this work we evaluate the potential for processing HOLODEC data by leveraging a combination of GPU hardware and machine learning with the eventual goal of improving HOLODEC processing speed and performance. We present a hologram processing algorithm, HolodecML, which utilizes a neural network segmentation model and computational parallelization to achieve these goals. HolodecML is trained using synthetically generated holograms based on a model of the instrument, and it predicts masks around particles found within reconstructed images. From these masks, the position and size of the detected particles can be characterized in three dimensions. In order to successfully process real holograms, we find we must apply a series of image corrupting transformations and noise to the synthetic images used in training. In this evaluation, HolodecML had comparable position and size estimations performance to the standard processing method, but it improved particle detection by nearly 20 % on several thousand manually labeled HOLODEC images. However, the particle detection improvement only occurred when image corruption was performed on the simulated images during training, thereby mimicking non-ideal conditions in the actual probe. The trained model also learned to differentiate artifacts and other impurities in the HOLODEC images from the particles, even though no such objects were present in the training data set. By contrast, the standard processing method struggled to separate particles from artifacts. HolodecML also leverages GPUs and parallel computing that enables large processing speed gains over serial and CPU-only based evaluation. Our results demonstrate that the machine-learning based framework may be a possible path to both improving and accelerating hologram processing. The novelty of the training approach, which leveraged noise as a means for parameterizing non-ideal aspects of the HOLODEC detector, could be applied in other domains where the theoretical model is incapable of fully describing the real-world operation of the instrument and accurate truth data required for supervised learning cannot be obtained from real-world observations.

Relating Binding Energy and Scattering Length of Cold Hybrid Ion‐Atom Systems

AbstractThe universal properties of the loosely bound vibrational states of cold hybrid ion‐atom systems are probed using a “scaling” approach. This approach is based on the use of numerical relations (a versus Dlast) between the binding energy (Dlast) of the highest vibrational state and the s‐wave scattering length (a) obtained by solving the appropriate Schrödinger equations with scaled interaction potentials. The actual probing is accomplished by evaluating the “a versus Dlast” relations for 6Li and 7Li in the ground electronic state using a set of ab initio potential energy curves from the literature. Although these curves provide strongly differing values of a and Dlast, the corresponding “a versus Dlast” relations closely coincide, thus enabling an accurate determination of scattering lengths directly from experimental binding energies and vice versa.

Establishment of a novel probe-based RT-qPCR approach for detection and quantification of tight junctions reveals age-related changes in the gut barriers of broiler chickens.

Tight junctions (TJs) play a dominant role in gut barrier formation, therefore, resolving the structures of TJs in any animal species is crucial but of major importance in fast growing broilers. They are regulated in molecular composition, ultrastructure and function by intracellular proteins and the cytoskeleton. TJ proteins are classified according to their function into barrier-forming, scaffolding and pore-forming types with deductible consequences for permeability. In spite of their importance for gut health and its integrity limited studies have investigated the TJs in chickens, including the comprehensive evaluation of TJs molecular composition and function in the chicken gut. In the actual study sequence-specific probes to target different TJ genes (claudin 1, 3, 5, 7, 10, 19, zonula occludens 1 (ZO1), occludin (OCLN) and tricellulin (MD2)) were designed and probe-based RT-qPCRs were newly developed. Claudin (CLDN) 1, 5, ZO1 and CLDN 3, 7, MD2 were engulfed in multiplex RT-qPCRs, minimizing the number of separate reactions and enabling robust testing of many samples. All RT-qPCRs were standardized for chicken jejunum and caecum samples, which enabled specific detection and quantification of the gene expression. Furthermore, the newly established protocols were used to investigate the age developmental changes in the TJs of broiler chickens from 1–35 days of age in the same organ samples. Results revealed a significant increase in mRNA expression between 14 and 21days of age of all tested TJs in jejunum. However, in caecum, mRNA expression of some TJs decreased after 1 day of age whereas some TJs mRNA remained constant till 35 days of age. Taken together, determining the segment-specific changes in the expression of TJ- proteins by RT-qPCR provides a deeper understanding of the molecular mechanisms underpinning pathophysiological changes in the gut of broiler chickens with various etiologies.

Probing signal design for enhanced damping estimation in power networks

Electromechanical oscillations are inherent to power networks. Although it is possible to partially damp these oscillations, it is impossible to eliminate them completely. This oscillatory behavior can lead to major breakdowns in power networks, especially when the damping is relatively low. It is therefore important to provide accurate estimations of the network’s damping values. These estimation can be obtained via system identification for which a probing signal needs to be designed. This paper presents a framework for designing a specific probing signal that is able to provide accurate damping estimations with a user-defined variance. A power spectrum of the probing signal is determined by solving an optimization problem with Linear Matrix Inequality constraints. The objective function is defined as a weighted sum of the probing signal’s power and a level of disturbance caused by probing the network. A desired level of the damping estimation’s variance is set as a constraint. The time-domain realization of the obtained power spectrum is described by a multisine, which is the actual probing signal applied to the network. The employed framework is demonstrated through nonlinear simulations using the Kundur with an embedded HVDC link and NORDIC 44 networks.

Impact of Rotor Blade Rotation of UAVs on Electromagnetic Field Measurements

In near-field (NF) measurements, the correction of the field probe influence is crucial for achieving high accuracy. With the increasing interest in antenna measurements based on unmanned aerial vehicles (UAVs), probe correction becomes essential also in this field. Here, the actual probe comprises the UAV together with the mounted probe antenna and in particular also the rotors which are spinning during flight. In this contribution, we investigate the field modulation caused by the rotating rotor blades of an UAV. We show that the arising modulation depends on the polarization of the used probe antenna as well as on the spatial separation from the UAV. It is also revealed that the rotor-caused modulation effect correlates with the rotation speed and that it is independent of the actual measurement frequency.

Pterophyllum scalare Genome Responses to Silver Nanoparticles

The rapid emergence of nanoparticles technology holds an abundant capacity for its future applications in the aquatic environment. In this study, P. scalare was selected to be a model to evaluate the probable effects of silver nanoparticles on the fish genome responses. The homogeneity among the estimated fish samples was evaluated via the analysis of inter simple sequence repeat (ISSR) markers. Fishes were reared for certain times under silver nanoparticle stresses. Four isozyme systems (esterase, malate dehydrogenase, superoxide dismutase, and alcohol dehydrogenase) and protein separations (using the sodium dodecyl sulfate-polyacrylamide gel electrophoresis) were assayed to identify biochemical genetic markers in three different fish tissues (eye, gill, and muscle) for all evaluated fish samples. No variations were appreciable among control and treated fish samples concerning protein separations. The separation of eye esterase and superoxide dismutase displays clear differences between the control and the treated fishes. The results proposed that exposure to silver Nanoparticles can change the number and intensity of some isozymes in certain fish body organs. Isozyme separations have proven to be actual probes of differential gene expression in various fish samples. More biochemical markers could be developed to monitor aquatic environmental health especially in the term of water pollution ranks in the future eco-toxicological investigations.

Robust optimization of multi-probe roundness measurement probe angles

Positional errors of a multi-probe roundness measurement frame will result in the probe angles deviating from the nominal angles. The actual probe angles can be accurately determined after placing the measurement frame using cross correlation or other methods. However, since multi-probe methods suffer from harmonic suppression, determining the angles is not enough for accurate reconstruction of the roundness profile, if the actual angles are situated in an area with poor harmonic characteristics. To find suitable areas for the probe angles to allow for deviations from the nominal angles, this paper presents a robust optimization for probe angles to avoid harmonic suppression regardless of errors in the probe angles. Suggestions for optimal probe angles are presented for the three-point and the four-point redundant diameter method.

Optical fibre thermometry using ratiometric green emission of an upconverting nanoparticle-polydimethylsiloxane composite

The thermally coupled green band emission from excited Er3+ ions has been used in the past to create optical thermometers, by doping the material in various types of media, particularly glasses. Glasses are known to be excellent hosts for Er3+ ions: however, high temperatures (>900 K) are usually required for doping these ions into glasses and a non-linear temperature response is often produced. In this work, the frequently encountered drawbacks of glass-based temperature sensors have been addressed by developing a temperature sensor created at a lower temperature (543 K), by dip-coating chemically synthesized upconverting nanoparticles (UCNP – NaYF4:(18%) Yb3+, (2%) Er3+) embedded in polydimethylsiloxane (PDMS) onto the tip of a 1000 μm optical fibre, to create the actual fibre probe. The sensor shows an excellent linear response (R2 = 0.991) over a very useful temperature range of 295 K – 473 K, with a sensitivity of 2.9 × 10-3 K-1, a temperature resolution of ± 2.7 K and response time of ∼ 5 seconds. Additionally, a probe was investigated where a pure upconverting nanoparticle powder was coated on the tip of optical fibre and its spectral and temperature response was obtained (and cross compared with that of UCNP-PDMS composite). The results obtained from the probe development work show that the UCNP-PDMS-coated optical fibre temperature sensor developed offers a better alternative to more conventional Er3+ doped glass-based temperature sensors, in terms of the thermal budget, the synthesis process and the ease of coating, creating as a result, a very linear device response.

Measurement of groove depth standards in the range 1 μm up to 1 mm (EURAMET project 1407)

A comparison measurement between 10 national metrology institutes on two types of depth setting standards was conducted using mostly tactile but also two optical instruments for measurement. Three etched silicon standards with depths of 5, 20 and 50 μm and one diamond turned nickel coated copper standard with depths of 200, 600 and 900 μm were measured. The cross section of the grooves was trapezoidal. Most of the participants confirmed their CMC entries. Since many measurements had to be made, contamination of the standards and heavy wear on the standards were also observed after the comparison was completed. The wear consists of indentation marks from stylus instruments on both types of standards and as many as 70 scratch marks on the nickel coated copper artefact used. This indicates that the contact pressure of the tactile measuring devices used by some partners was too high. This can be caused by a too high probing force or a too small probing tip radius. Thus, for future comparisons the actual probing force and actual tip radius need to be measured during the comparison by the participants to assure that the recommended values (2 μm tip radius and 0.7 mN probing force) are not exceeded. The recently published German standard DIN 32567-3 "Determination of the influence of materials on the optical and tactile dimensional metrology - Part 3: Derivation of correction values for tactile measuring devices" describes methods to do both.Main textTo reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/.The final report has been peer-reviewed and approved for publication by the CCL, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Augmented reality and artificial intelligence-assisted surgical navigation: Technique and cadaveric feasibility study.

Purpose:Augmented reality-based image overlay of virtual bony spine anatomy can be projected onto real spinal anatomy using computer tomography-generated DICOM images acquired intraoperatively. The aim of the study was to develop a technique and assess the accuracy and feasibility of lumbar vertebrae pedicle instrumentation using augmented reality-assisted surgical navigation.Subjects and Methods:An augmented reality and artificial intelligence (ARAI)-assisted surgical navigation system was developed. The system consists of a display system which hovers over the surgical field and projects three-dimensional (3D) medical images corresponding with the patient's anatomy. The system was registered to the cadaveric spine using an optical tracker and arrays with reflective markers. The virtual image overlay from the ARAI system was compared to 3D generated images from intraoperative scans and used to percutaneously navigate a probe to the cortex at the corresponding pedicle starting point. Intraoperative scan was used to confirm the probe position. Virtual probe placement was compared to the actual probe position in the bone to determine the accuracy of the navigation system.Results:Four cadaveric thoracolumbar spines were used. The navigated probes were correctly placed in all attempted levels (n = 24 levels), defined as Zdichavsky type 1a, Ravi type I, and Gertzbein type 0. The virtual overlay image corresponded to the 3D generated image in all the tested levels.Conclusions:The ARAI surgical navigation system correctly and accurately identified the starting points at all the attempted levels. The virtual anatomy image overlay precisely corresponded to the actual anatomy in all the tested scenarios. This technology may lead more uniform outcomes between surgeons and decrease minimally invasive spine surgery learning curves.

Open LabBot and RmsiGUI: Community development kit for sampling automation and ambient imaging

Building novel analytical systems requires various elements: Sensors, a sampling system and data evaluation software. For emerging technologies, such as ambient ionization mass spectrometry (AIMS), the assembly of a functional prototype is often more time-consuming than developing the actual probes. The modification of commercial platforms for testing hardware is usually not possible due to technical and legal restrictions. Therefore, we designed a robotic platform, which is based on RepRap 3D-printer components, and therefore easy to adopt for custom set-ups. Adjustable rails in an aluminium frame construction facilitate the mounting of additional parts such as sensors, probes, or optical components. The Open LabBot uses industry-standard G-code for its control. Its simple syntax facilitates the programming of the movement. We developed two programs for the robot control and mass spectrometry imaging: “LABI-Imaging” for synchronizing the robot movements and MS data acquisition and “RmsiGUI”, a software solution for the complete AIMS workflow. We proved the functionality of the system by the automated sampling and classification of essential oils with a PlasmaChip probe. Further, we performed an AIMSI imaging experiment of a lime slice with laser desorption low-temperature plasma (LD-LTP) ionization, demonstrating the integration of the complete workflow in RmsiGUI. The design of the Open LabBot and the software are released under open licenses to promote their use and adoption in the instrument developers’ community.

Analysis of transient-absorption pump-probe signals of nonadiabatic dissipative systems: "Ideal" and "real" spectra.

We introduce and analyze the concept of the "ideal" time and frequency resolved transient-absorption pump-probe (PP) signal. The ideal signal provides the most direct link between the "real" (measurable) PP signal and the material system dynamics. The simulation of PP signals involves two steps. (i) The ideal signal, which exhibits perfect time and frequency resolution, is calculated. For this purpose, the probe pulse is replaced by an auxiliary continuous-wave pulse. (ii) The real signal is obtained by the convolution of the ideal signal with the appropriate time- and frequency-gate function, which depends on the envelope of the actual probe pulse. This concept has been used to simulate integral and dispersed PP signals for a model system exhibiting nonadiabatic and dissipative dynamics. The ideal signal is computed with the two-pulse equation-of-motion phase-matching approach which has been extended to take excited-state absorption into account. We demonstrate how the ideal signal, an object exhibiting the features of moving wave packets as well as stationary spectra, is related to real signals detected with short (good temporal resolution) or long (good frequency resolution) probe pulses.