Sensors In Close Proximity Research Articles

Joint Particle Detection and Analysis by a CNN and Adaptive Norm Minimization Approach.

Optical flow cytometry is used as the gold standard in single cell function diagnostics with the drawback of involving high complexity and operator costs. Magnetic flow cytometers try to overcome this problem by replacing optical labeling with magnetic nanoparticles to assign each cell a magnetic fingerprint. This allows operators to obtain rich cell information from a biological sample with minimal sample preparation at near in-vivo conditions in a decentralized environment. A central task in flow cytometry is the determination of cell concentrations and cell parameters, e.g. hydrodynamic diameter. For the acquisition of this information, signal processing is an essential component. Previous approaches mainly focus on the processing of one-cell signals, leaving out superimposed signals originating from cells passing the magnetic sensors in close proximity. In this work, we present a framework for joint cell/particle detection and analysis, which is capable of processing one-cell as well as multi-cell signals. We employ deep learning and compressive sensing in this approach, which involves the minimization of an adaptive norm. We evaluate our method on simulated and experimental signals, the latter being obtained with polymer microparticles. Our results show that the framework is capable of counting cells with a relative error smaller than 2%. Inference of cell parameters works reliably at both low and high noise levels.

Behaviour of Ironless Inductive Position Sensors in Close Proximity to Each Other

Behaviour of Ironless Inductive Position Sensors in Close Proximity to Each Other

MCH-EOR: Multi-objective Cluster Head Based Energy-aware Optimized Routing algorithm in Wireless Sensor Networks

Hierarchical Wireless Sensor Networks (WSNs) have got vital application domains in modern era especially in monitoring and tracking of events, and without human intervention. In WSN, sensor nodes are characterized to have short life span due to continuous sensing and consequently the battery drains quickly. Under heavy traffic condition, sensors in close proximity to sink die quickly and initiate energy-hole problem. Thus, optimal usage of available energy is a key challenge in WSN assisted applications. A precise clustering and optimal path selection from sensor nodes to sink has become extremely important to preserve energy. Keeping this in view, the paper presents a Multi-Objective Based Clustering and Sailfish Optimizer (SFO) guided routing method to sustain energy efficiency in WSNs. In it the Cluster Head (CH) is selected, based on effective fitness function which is formulated from multiple objectives. It helps to minimize energy consumption and reduces number of dead sensor nodes. After CH selection, SFO is used to select an optimal path to sink node for data transmission. The proposed approach is analytically analyzed and results are compared with the similar existing approaches namely, Grey wolf optimization (GWO), Genetic algorithm (GA), Ant Lion optimization (ALO), and Particle Swarm Optimization (PSO) in terms of energy consumption, throughput, packet delivery ratio, and network lifetime. The simulation results show that proposed method has performed 21.9% and 24.4% better in terms of energy consumption and number of alive sensor nodes respectively when compared to GWO. Further, it shows significantly better results than other optimization-based approaches.

Six‐Axis Ground Motion Measurements of Caldera Collapse at Kīlauea Volcano, Hawai'i—More Data, More Puzzles?

AbstractNear‐field recordings of large earthquakes and volcano‐induced events using traditional seismological instrumentation often suffer from unaccounted effects of local tilt and saturation of signals. Recent hardware advances have led to the development of the blueSeis‐3A, a very broadband, highly sensitive rotational motion sensor. We installed this sensor in close proximity to permanently deployed classical instrumentation (i.e., translational seismometer, accelerometer, and tiltmeter) at the Hawaiian Volcano Observatory (USGS). There, we were able to record three ~Mw 5 earthquakes associated with large collapse events during the later phase of the 2018 Kīlauea summit eruption. Located less than 2 km from the origins of these sources, the combined six‐axis translational and rotational measurements revealed clear static rotations around all three coordinate axes. With these six component recordings, we have been able to reconstruct the complete time history of ground motion of a fixed point during an earthquake for the first time.

Performance optimization of capacitive motion sensing (CMS) system for intra-fraction motion detection during stereotactic radiosurgery

The purpose of this investigation is to improve intra-fractional motion detection during cranial stereotactic radiosurgery with a novel capacitive motion sensing (CMS) system. Previous work showed that a capacitive detection system, based on a MPR121 capacitance-to-digital converter, provided a number of advantages over existing patient imaging systems used in the clinic, by uniquely offering ionizing-radiation-free and continuous monitoring without modification to the immobilization mask or treatment room. However, in order to provide submillimeter detection accuracy, the MPR121-based CMS system required relatively large sensors in close proximity to the patient. Therefore, the aim of this investigation was to improve sensitivity of the system, allowing reduction in sensor size and preserving its stable operation in the linear accelerator environment. For this, we developed, characterized and compared motion detection capabilities of four CMS systems based on different capacitance-to-digital converters: MPR121, CPT212B, FDC1004 and FDC2214. Among all candidates, the FDC2214-based system was found to uniquely combine accurate 3D motion detection in real time, with stable performance under ionizing radiation. It exhibited an order of magnitude improvement in sensitivity in comparison with the proof-of-study system, allowing a spatial precision as low as 0.3 mm, and its overall performance was found to satisfy the AAPM practice guidelines of positioning tolerance within 1 mm. Furthermore, the high sensitivity of the system allows both reduction of the sensor area and location more distant from the patient surface, which are key improvements with regard to development of a clinical device.

Near field non-invasive electrophysiology of retrotrapezoid nucleus using amperometric cation sensor

Central chemoreception is the process whereby the brainstem senses blood gas levels and adjusts homeostatic functions such as breathing and cardiovascular tone accordingly. Rodent evidence suggests that the retrotrapezoid nucleus (RTN) is a master regulator of central chemoreception, in particular, through direct sensation of acidosis induced by CO2 levels. The oscillatory dynamics caused by pH changes as sensed by the RTN surface and its relationship to the fluctuations in cation flux is not clearly understood due to the current limitations of electrophysiology tools and this article presents our investigations to address this need. A cation selective sensor fabricated from polypyrrole doped with dodecyl benzenesulfonate (PPy (DBS)) is placed over RTN in an ex-vivo en bloc brain and changes in cation concentration in the diffusion limited region above the RTN is measured due to changes in externally imposed basal pH. The novelty of this technique lies in its feasibility to detect cation fluxes from the cells in the RTN region without having to access either sides of the cell membrane. Owing to the placement of the sensor in close proximity to the tissue, we refer to this technique as near-field electrophysiology. It is observed that lowering the pH in the physiological range (7.4–7.2) results in a significant increase in cation concentration in the vicinity of RTN with a median value of ~5 μM. The utilization of such quantifiable measurement techniques to detect sub-threshold brain activity may help provide a platform for future neural network architectures. Findings from this paper present a quantifiable, sensitive, and robust electrophysiology technique with minimal damage to the underlying tissue.

Wave separation and pipeline condition assessment using in-pipe fibre optic pressure sensors

Abstract The use of two pressure transducers in close proximity can enable the separation of the directional travelling pressure waves in pipelines. However, the implementation of this measurement strategy in real water pipes is difficult due to the lack of closely located access points. This paper reports the use of a customised in-pipe fibre optic pressure sensor array for hydraulic transient wave separation and pipeline condition assessment. The fibre optic pressure sensor array can be inserted into a pressurised pipeline through a single access point. The array consists of multiple fibre Bragg grating (FBG)-based pressure sensors in close proximity (∼0.5 m apart). A previously developed wave separation algorithm is adapted to analyse the transient pressure measurement from the FBG sensors. The resultant directional pressure waves are then used to detect pipe sections with a thinner wall thickness. A challenge is the influence of the in-pipe fibre optic sensing cable on the transient pressure measurement. The impact is analysed and adjustments to the pipeline condition assessment algorithm are undertaken to resolve the issue. The successful experimental application verifies the usefulness of the in-pipe fibre optic sensor array, which can facilitate transient-based pipeline condition assessment for buried water pipes with limited access points.

Integrating proximal broad-band vegetation indices and carbon fluxes to model gross primary productivity in a tropical dry forest

The measurement of carbon exchange between vegetation and the atmosphere is vital to quantify the impact of environmental variables on the carbon sequestration capacity of forests, and to predict how they will respond to future climate. In this study we use proximal remote sensing, defined as observations made from non-contact radiometric or imaging sensors in close proximity to the forest canopy (10–20 m), as an intermediate upscaling tool between direct measurements of carbon fluxes and satellite-derived estimations of primary productivity in a tropical dry forest (TDF) in Jalisco, Mexico. Two broad-band vegetation indices (VIs), the normalized difference VI and the enhanced vegetation index 2 (EVI2), were calculated from proximally sensed canopy properties, validated with field estimates of the fraction of absorbed photosynthetically active radiation by photosynthetic tissue (fAPARgreen), and compared to estimates of gross primary productivity (GPP) and net ecosystem exchange of CO2, measured from a flux tower. The VIs captured the phenology of the TDF, both under typical summer rainfall and during an atypically-dry wet season in El Niño of 2009. The VIs also tracked a secondary leaf-flushing in the dry season of 2010. Our study suggests that (1) VIs are the best predictors of gross carbon uptake, able to explain up to 86% of variations in GPP; (2) VIs are accurate predictors of the photosynthetic capacity of green tissue, able to explain up to 99% of fAPARgreen variation; and (3) VIs and soil water content can be used to develop an empirical model that captures the seasonal trajectory of GPP from high respiration after the rain pulses, to rapid leaf development, and finally to slow senescence as the soil dries out. Proximal remote sensing constitutes a useful tool to link field-base measurements of carbon fluxes to satellite- or airborne-derived estimates of carbon exchange.

Optical magnetic detection of single-neuron action potentials using quantum defects in diamond

Magnetic fields from neuronal action potentials (APs) pass largely unperturbed through biological tissue, allowing magnetic measurements of AP dynamics to be performed extracellularly or even outside intact organisms. To date, however, magnetic techniques for sensing neuronal activity have either operated at the macroscale with coarse spatial and/or temporal resolution-e.g., magnetic resonance imaging methods and magnetoencephalography-or been restricted to biophysics studies of excised neurons probed with cryogenic or bulky detectors that do not provide single-neuron spatial resolution and are not scalable to functional networks or intact organisms. Here, we show that AP magnetic sensing can be realized with both single-neuron sensitivity and intact organism applicability using optically probed nitrogen-vacancy (NV) quantum defects in diamond, operated under ambient conditions and with the NV diamond sensor in close proximity (∼10 µm) to the biological sample. We demonstrate this method for excised single neurons from marine worm and squid, and then exterior to intact, optically opaque marine worms for extended periods and with no observed adverse effect on the animal. NV diamond magnetometry is noninvasive and label-free and does not cause photodamage. The method provides precise measurement of AP waveforms from individual neurons, as well as magnetic field correlates of the AP conduction velocity, and directly determines the AP propagation direction through the inherent sensitivity of NVs to the associated AP magnetic field vector.

The SESAME/CASSE instrument listening to the MUPUS PEN insertion phase on comet 67P/Churyumov–Gerasimenko

After the final landing of Philae at the Abydos site on comet 67/P Churyumov–Gerasimenko, the MUPUS (Multipurpose Sensors for Surface and Sub-Surface Science) device started hammering itself into the cometary ground on 14th November 2014, and continued hammering for more than 3h. During this period, the CASSE (Comet Acoustic Surface Sounding Experiment) instrument, part of SESAME (Surface Electric Sounding and Acoustic Monitoring Experiment), was listening to the hammer strokes of MUPUS, which was the strongest available source for a seismic–acoustic experiment to determine mechanical properties of the ground.All sensors survived the multiple touchdowns of Philae undamaged and provided recordings of 14 hammer strokes at audible frequencies. The data suggests that Philae was slightly rocking or swinging during the initial phase of the experiment, finally finding an attitude that not only stopped this motion but also improved the coupling of sensors to the ground and thus the recordings.The experiment provides several lessons that might be useful for the development of similar experiments on future spacecraft. The most serious issues concerning the CASSE recordings are clock accuracy and synchronicity and the timing of the source. Future designs may want to consider additional sensors in close proximity to the source, and direct communication between experiments to overcome this. The present design allows the evaluation of arrival time differences only, rather than absolute travel times.In this contribution, we focus on the technical and operational aspects of this experiment. A scientific evaluation of the data received will follow in a second paper.

Feasibility assessment of MEMS oscillators for GNSS receivers

We analyze results from using a temperature-sensing MEMS oscillator as frequency source for the front end of a software-based GNSS receiver. Results show that although MEMS oscillators are highly sensitive to temperature, GNSS receivers can still make use of them even without any form of temperature information or compensation. Nevertheless, using a temperature sensor in close proximity to the resonator can significantly decrease acquisition time and improve tracking performance if the temperature measurements are properly filtered to remove noise. In this case, no negative effect on the measured carrier-to-noise density ratio was detected, and phase-locked tracking of strong signals was possible over a temperature range of ź40 to +85 °C.

Breast cancer detection using interferometric MUSIC: experimental and numerical assessment.

In microwave breast cancer detection, it is often beneficial to arrange sensors in close proximity to the breast. The resultant coupling generally changes the antenna response. As an a priori characterization of the radio frequency system becomes difficult, this can lead to severe degradation of the detection efficacy. The purpose of this paper is to demonstrate the advantages of adopting an interferometric multiple signal classification (I-MUSIC) approach due to its limited dependence from a priori information on the antenna. The performance of I-MUSIC detection was measured in terms of signal-to-clutter ratio (SCR), signal-to-mean ratio (SMR), and spatial displacement (SD) and compared to other common linear noncoherent imaging methods, such as migration and the standard wideband MUSIC (WB-MUSIC) which also works when the antenna is not accounted for. The data were acquired by scanning a synthetic oil-in-gelatin phantom that mimics the dielectric properties of breast tissues across the spectrum 1-3 GHz using a proprietary breast microwave multi-monostatic radar system. The phantom is a multilayer structure that includes skin, adipose, fibroconnective, fibroglandular, and tumor tissue with an adipose component accounting for 60% of the whole structure. The detected tumor has a diameter of 5 mm and is inserted inside a fibroglandular region with a permittivity contrast εr-tumor/εr-fibroglandular < 1.5 over the operating band. Three datasets were recorded corresponding to three antennas with different coupling mechanisms. This was done to assess the independence of the I-MUSIC method from antenna characterizations. The datasets were processed by using I-MUSIC, noncoherent migration, and wideband MUSIC under equivalent conditions (i.e., operative bandwidth, frequency samples, and scanning positions). SCR, SMR, and SD figures were measured from all reconstructed images. In order to benchmark experimental results, numerical simulations of equivalent scenarios were carried out by using CST Microwave Studio. The three numerical datasets were then processed following the same procedure that was designed for the experimental case. Detection results are presented for both experimental and numerical phantoms, and higher performance of the I-MUSIC method in comparison with the WB-MUSIC and noncoherent migration is achieved. This finding is confirmed for the three different antennas in this study. Although a delocalization effect occurs, experimental datasets show that the signal-to-clutter ratio and the signal-to-mean performance with the I-MUSIC are at least 5 and 2.3 times better than the other methods, respectively. The numerical datasets calculated on an equivalent phantom for cross-testing confirm the improved performance of the I-MUSIC in terms of SCR and SMR. In numerical simulations, the delocalization effect is dramatically reduced up to an SD value of 1.61 achieved with the I-MUSIC in combination with the antipodal Vivaldi antenna. This shows that mechanical uncertainties are the main reason for the delocalization effect in the measurements. Experimental results show that the I-MUSIC generates images with signal-to-clutter levels higher than 5.46 dB across all working conditions and it reaches 7.84 dB in combination with the antipodal Vivaldi antenna. Numerical simulations confirm this trend and due to ideal mechanical conditions return a signal-to-clutter level higher than 7.61 dB. The I-MUSIC largely outperforms the methods under comparison and is able to detect a 5-mm tumor with a permittivity contrast of 1.5.

A structural framework for interpretation of four-electrode microimpedance spectra in cardiac tissue.

Renewed interest in the four-electrode method for identification of passive electrical properties in cardiac tissue has been sparked by a recognition that measurements made with sensors in close proximity are frequency dependent. Therefore, resolution of four-electrode microimpedance spectra (4EMS) may provide an opportunity for routine identification of passive electrical properties for the interstitial and intracellular compartments using only interstitial access. The present study documents a structural framework in which the tissue resistivity (ρt) and reactivity (xt) that comprise spectra are computed using interstitial and intracellular microimpedance distributions that account for differences in compartment size, anisotropic electrical properties in each compartment and electrode separations. We used this framework to consider 4EMS development with relatively wide (d=1 mm) and fine (d=250 μm) electrode separations and sensors oriented along myocyte axes, across myocyte axes and intermediate between those axes.

Integral three-dimensional image capture equipment with closely positioned lens array and image sensor

We have developed a compact integral three-dimensional (3D) imaging equipment that positions the lens array and image sensor in close proximity to each other. In the conventional scheme, a camera lens is used to project the elemental images generated by the lens array onto the image sensor. In contrast, the imaging equipment presented here combines the lens array and image sensor into one unit and makes no use of a camera lens. This scheme eliminates the resolution deterioration and distortion caused by the use of a camera lens and improves, in principle, the quality of the reconstructed 3D image. We captured objects with this imaging equipment and displayed the reconstructed 3D images using display equipment consisting of a liquid crystal panel and a lens array. The reconstructed 3D images were found to have appropriate motion parallax.

A microfluidic device integrating plasmonic nanodevices for Raman spectroscopy analysis on trapped single living cells

In this work we developed a microfluidic device integrating nanoplasmonic devices combined with fluidic trapping regions. The microfuidic traps allow to capture single cells in areas where plasmonic sensors are placed. In this way it is possible to perform Enhanced Raman analysis on the cell membranes. Moreover, by changing direction of the flux it is possible to change the orientation of the cell in the trap, so that it is possible to analyze different points of the membrane of the same cell. We shows an innovative procedure to fabricate and assembly the microfluidic device which combine photolithography, focused ion beam machining, and hybrid bonding between a polymer substrate and lid of Calcium fluoride. This procedure is compatible with the fabrication of the plasmonic sensors in close proximity of the microfluidic traps. Moreover, the use of Calcium fluoride as lid allows full compatibility with Raman measurements producing negligible Raman background signal and avoids Raman artifacts. Finally, we performed Raman analysis on cells to monitor their oxidative stress under particular non physiological conditions.

Nanoscale magnetic imaging of a single electron spin under ambient conditions

The detection of ensembles of spins under ambient conditions has revolutionized the biological, chemical, and physical sciences through magnetic resonance imaging and nuclear magnetic resonance. Pushing sensing capabilities to the individual-spin level would enable unprecedented applications such as single molecule structural imaging; however, the weak magnetic fields from single spins are undetectable by conventional far-field resonance techniques. In recent years, there has been a considerable effort to develop nanoscale scanning magnetometers, which are able to measure fewer spins by bringing the sensor in close proximity to its target. The most sensitive of these magnetometers generally require low temperatures for operation, but measuring under ambient conditions (standard temperature and pressure) is critical for many imaging applications, particularly in biological systems. Here we demonstrate detection and nanoscale imaging of the magnetic field from a single electron spin under ambient conditions using a scanning nitrogen-vacancy (NV) magnetometer. Real-space, quantitative magnetic-field images are obtained by deterministically scanning our NV magnetometer 50 nanometers above a target electron spin, while measuring the local magnetic field using dynamically decoupled magnetometry protocols. This single-spin detection capability could enable single-spin magnetic resonance imaging of electron spins on the nano- and atomic scales and opens the door for unique applications such as mechanical quantum state transfer.

Secure Cooperative Sensing in IEEE 802.22 WRANs Using Shadow Fading Correlation

Cooperative (or distributed) sensing has been recognized as a viable means to enhance the incumbent signal detection by exploiting the diversity of sensors. However, it is challenging to secure such distributed sensing due mainly to the unique features of dynamic spectrum access networks-openness of low-layer protocol stacks in software-defined radio devices and the absence of interactions/coordination between primary and secondary devices. To meet this challenge, we propose an attack-tolerant distributed sensing protocol (ADSP) for DTV signal detection in IEEE 802.22 WRANs, under which sensors in close proximity are grouped as a cluster, and sensors within a cluster cooperate to safeguard the integrity of sensing. The heart of ADSP is a novel filter based on shadow-fading correlation, by which the fusion center cross-validates reports from the sensors to identify and penalize abnormal sensing reports. By realizing this correlation filter, ADSP significantly reduces the impact of an attack on the performance of distributed sensing, while incurring minimal processing and communication overheads. ADSP also guarantees the detectability requirements of 802.22 to be met even with the presence of sensing report manipulation attacks by scheduling sensing within the framework of sequential hypothesis testing. The efficacy of ADSP is validated on a realistic 2D shadow-fading field. Our extensive simulation-based study shows that ADSP reduces the false-alarm rate by 99.2 percent while achieving 97.4 percent of maximum achievable detection rate, and meets the detection requirements of IEEE 802.22 in various attack scenarios.

An Efficient Method for Constructing Underwater Sensor Barriers

Anti-submarine warfare(ASW) is a critical challenge for maintaining a fleet presence in hostile areas. Technology advancement has allowed submarines to evade standard sonar detection. A viable alternative is to place magnetic or acoustic sensors in close proximity to possible underwater pathways of submarines. This approach may require deploying large-scale underwater sensor networks to form 3-dimensional barriers. We present new results on sensor barriers for 3-dimensional sensor networks. We first show that when sensor locations follow a Poisson Point Process then sensor barriers in a large 3- dimensional fixed emplacement sensor field are unlikely to exist. We use the notion of 3-dimensional stealth distance to measure how far a submarine can travel in a sensor network without being detected. We devise an energy-conserving scheme to construct 3- dimensional barriers using mobile sensors. We focus on develop- ing an energy efficient matching of mobile sensors to cover grid points using distributed auction algorithms. Specifically, we try to minimize the maximum travel distance between any sensor and its assigned grid point. Through simulation we show in comparison to the optimal solution, the distributed auction based approach offers reduced computation time and similar maximum travel distance. This provides a promising new approach to constructing barriers in 3-dimensional sensor networks.

Dynamic strain measurements of a cantilever using the improved bonding fiber Bragg grating

For a surface mounted fiber Bragg grating (FBG) strain sensor, this study used an improved bonding method that distributes cement only on the two ends of the grating and leaves the grating free from cement. According to a recent numerical study, for a conventional surface mounted FBG strain sensor its relationship between average strains (within its glued grating) and voltage signals is nonlinear and changeable depending on the variation patterns of strain gradients (within its glued grating) in a strain history. By contrast, the relationship for the improved bonding one is linear because of the constant zero strain gradient within the glue-free grating. To experimentally verify the linear relationship for the improved bonding fiber Bragg grating (IBFBG), this study set up a cantilever with both the IBFBG and a resistance strain gauge surface mounted in close proximity, and the vibration responses were induced by impactions of a free-falling steel ball on the cantilever's surface. Experimental results indicate that dynamic calibrations of an IBFBG by using a commonly used resistance strain gauge are possible because both sensors in close proximity have their changes of voltage signals almost proportional to each other.

Scanning Hall Probe Microscopy (SHPM) Using Quartz Crystal AFM Feedback

Scanning Hall Probe Microscopy (SHPM) is a quantitative and non-invasive technique for imaging localized surface magnetic field fluctuations such as ferromagnetic domains with high spatial and magnetic field resolution of approximately 50 nm and 7 mG/Hz(1/2) at room temperature. In the SHPM technique, scanning tunneling microscope (STM) or atomic force microscope (AFM) feedback is used to keep the Hall sensor in close proximity of the sample surface. However, STM tracking SHPM requires conductive samples; therefore the insulating substrates have to be coated with a thin layer of gold. This constraint can be eliminated with the AFM feedback using sophisticated Hall probes that are integrated with AFM cantilevers. However it is very difficult to micro fabricate these sensors. In this work, we have eliminated the difficulty in the cantilever-Hall probe integration process, just by gluing a Hall Probe chip to a quartz crystal tuning fork force sensor. The Hall sensor chip is simply glued at the end of a 32.768 kHz or 100 kHz Quartz crystal, which is used as force sensor. An LT-SHPM system is used to scan the samples. The sensor assembly is dithered at the resonance frequency using a digital Phase Locked Loop circuit and frequency shifts are used for AFM tracking. SHPM electronics is modified to detect AFM topography and the frequency shift, along with the magnetic field image. Magnetic domains and topography of an Iron Garnet thin film crystal, NdFeB demagnetised magnet and hard disk samples are presented at room temperature. The performance is found to be comparable with the SHPM using STM feedback.