WILBERT

Description: Presents the table of contents for this issue of this publication.

Description: Last July, when a Chinese Long March 5 rocket lifted off from the country’s newest spaceport, the Wenchang Space Launch Center on the island of Hainan, the vehicle's official mission was to place an experimental communications satellite into orbit. The launch, though, had a secondary purpose: It was to be a final test before the Long March 5, China's newest and largest rocket, was entrusted with the country's most ambitious science mission ever.

Description: Sometime later this year, dozens of robots will spring into action at a new factory in Little Rock, Ark. The plant will not make cars or electronics, nor anything else that robots are already producing these days. Instead it will make T-shirts-lots of T-shirts. When fully operational, these sewing robots will churn them out at a dizzying rate of one every 22 seconds. For decades, the automation of the sewing of garments has vexed roboticists. Conventional robots excel at manipulating rigid objects but are rather inept at handling soft,flexible materials like fabric. Early attempts to automate sewing included treating pieces of cloth with starch to temporarily make them stiff, allowing a robot to manipulate them as if they were steel sheets. This and other approaches, however, never became commercially viable, mainly because the clothing industry has resisted automation by relying on cheap labor in developing countries.

Description: Geometric distortion induced by the main B0 field disrupts the consistency of fetal echo planar imaging (EPI) data, on which diffusion and functional magnetic resonance imaging is based. In this paper, we present a novel data-driven method for simultaneous motion and distortion correction of fetal EPI. A motion-corrected and reconstructed T2 weighted single shot fast spin echo (ssFSE) volume is used as a model of undistorted fetal brain anatomy. Our algorithm interleaves two registration steps: estimation of fetal motion parameters by aligning EPI slices to the model; and deformable registration of EPI slices to slices simulated from the undistorted model to estimate the distortion field. The deformable registration is regularized by a physically inspired Laplacian constraint, to model distortion induced by a source-free background B0 field. Our experiments show that distortion correction significantly improves consistency of reconstructed EPI volumes with ssFSE volumes. In addition, the estimated distortion fields are consistent with fields calculated from acquired field maps, and the Laplacian constraint is essential for estimation of plausible distortion fields. The EPI volumes reconstructed from different scans of the same subject were more consistent when the proposed method was used in comparison with EPI volumes reconstructed from data distortion corrected using a separately acquired B0 field map.

Description: In this paper, we propose a generalized joint sparsity regularization prior and reconstruction framework for the synergistic reconstruction of positron emission tomography (PET) and under sampled sensitivity encoded magnetic resonance imaging data with the aim of improving image quality beyond that obtained through conventional independent reconstructions. The proposed prior improves upon the joint total variation (TV) using a non-convex potential function that assigns a relatively lower penalty for the PET and MR gradients, whose magnitudes are jointly large, thus permitting the preservation and formation of common boundaries irrespective of their relative orientation. The alternating direction method of multipliers (ADMM) optimization framework was exploited for the joint PET-MR image reconstruction. In this framework, the joint maximum a posteriori objective function was effectively optimized by alternating between well-established regularized PET and MR image reconstructions. Moreover, the dependency of the joint prior on the PET and MR signal intensities was addressed by a novel alternating scaling of the distribution of the gradient vectors. The proposed prior was compared with the separate TV and joint TV regularization methods using extensive simulation and real clinical data. In addition, the proposed joint prior was compared with the recently proposed linear parallel level sets (PLSs) method using a benchmark simulation data set. Our simulation and clinical data results demonstrated the improved quality of the synergistically reconstructed PET-MR images compared with the unregularized and conventional separately regularized methods. It was also found that the proposed prior can outperform both the joint TV and linear PLS regularization methods in assisting edge preservation and recovery of details, which are otherwise impaired by noise and aliasing artifacts. In conclusion, the proposed joint sparsity regularization within the presented a- ADMM reconstruction framework is a promising technique, nonetheless our clinical results showed that the clinical applicability of joint reconstruction might be limited in current PET-MR scanners, mainly due to the lower resolution of PET images.

Description: We present a novel approach for improving the shape statistics of medical image objects by generating correspondence of skeletal points. Each object’s interior is modeled by an s-rep, i.e., by a sampled, folded, two-sided skeletal sheet with spoke vectors proceeding from the skeletal sheet to the boundary. The skeleton is divided into three parts: the up side, the down side, and the fold curve. The spokes on each part are treated separately and, using spoke interpolation, are shifted along that skeleton in each training sample so as to tighten the probability distribution on those spokes’ geometric properties while sampling the object interior regularly. As with the surface/boundary-based correspondence method of Cates et al. , entropy is used to measure both the probability distribution tightness and the sampling regularity, here of the spokes’ geometric properties. Evaluation on synthetic and real world lateral ventricle and hippocampus data sets demonstrate improvement in the performance of statistics using the resulting probability distributions. This improvement is greater than that achieved by an entropy-based correspondence method on the boundary points.

Description: Magnetic particle imaging (MPI) is a promising new tomographic imaging method to detect the spatial distribution of superparamagnetic iron-oxide nanoparticles (SPIOs). The aim of this paper was to investigate the potential of MPI to quantify artificial stenoses in vessel phantoms. Custom-made stenosis phantoms (length 40 mm; inner diameter 8 mm) with different degrees of stenosis (0%, 25%, 50%, 75%, and 100%) were scanned in a custom-built MPI scanner (in-plane resolution: ~1–1.5 mm and field of view: 65 $times $ 29 $times $ 29 mm 3 ). Phantoms were filled with diluted Feru-carbotran [SPIO agent, 5 mmol (Fe)/l]. Each measurement (overall acquisition time: 20 ms per image, 400 averages) was repeated ten times to assess reproducibility. The MPI signal was used for semi-automatic stenosis quantification. Two stenosis evaluation approaches were compared based on the signal intensity profile alongside the stenosis phantoms. Using a novel multi-step image evaluation approach, MPI allowed for accurate quantification of different stenosis grades. While low grade stenoses were slightly over-estimated, high grade stenoses were slightly underestimated. In particular, the 0%, 25%, and 50% stenosis phantoms revealed a 6.2% ± 0.8, 25.7% ± 1.0, and 48.0% ± 1.5 stenosis, respectively. The higher grade 75% stenosis phantom revealed a 73.3% ± 2.8 and the 100% stenosis phantom a 95.8%± 1.9 stenosis. MPI accu- ately visualized and quantified different stenosis grades in vessel phantoms with high reproducibility demonstrating its great potential for fast and radiation-free preclinical cardiovascular imaging.

Description: Ultrasound molecular imaging (USMI) is accomplished by detecting microbubble (MB) contrast agents that have bound to specific biomarkers, and can be used for a variety of imaging applications, such as the early detection of cancer. USMI has been widely utilized in preclinical imaging in mice; however, USMI in humans can be challenging because of the low concentration of bound MBs and the signal degradation caused by the presence of heterogenous soft tissue between the transducer and the lesion. Short-lag spatial coherence (SLSC) beamforming has been proposed as a robust technique that is less affected by poor signal quality than standard delay-and-sum (DAS) beamforming. In this paper, USMI performance was assessed using contrast-enhanced ultrasound imaging combined with DAS (conventional CEUS) and with SLSC (SLSC-CEUS). Each method was characterized by flow channel phantom experiments. In a USMI-mimicking phantom, SLSC-CEUS was found to be more robust to high levels of additive thermal noise than DAS, with a 6dB SNR improvement when the thermal noise level was +6dB or higher. However, SLSC-CEUS was also found to be insensitive to increases in MB concentration, making it a poor choice for perfusion imaging. USMI performance was also measured in vivo using VEGFR2-targeted MBs in mice with subcutaneous human hepatocellular carcinoma tumors, with clinical imaging conditions mimicked using a porcine tissue layer between the tumor and the transducer. SLSC-CEUS improved the SNR in each of ten tumors by an average of 41%, corresponding to 3.0dB SNR. These results indicate that the SLSC beamformer is well-suited for USMI applications because of its high sensitivity and robust properties under challenging imaging conditions.

Description: Histotripsy utilizes focused ultrasound to generate bubble clouds for transcutaneous tissue liquefaction. Bubble activity maps are under development to provide image guidance and monitor treatment progress. The aim of this paper was to investigate the feasibility of using plane wave B-mode and passive cavitation images to be used as binary classifiers of histotripsy-induced liquefaction. Prostate tissue phantoms were exposed to histotripsy pulses over a range of pulse durations (5– $20~mu text{s}$ ) and peak negative pressures (12–23 MPa). Acoustic emissions were recorded during the insonation and beamformed to form passive cavitation images. Plane wave B-mode images were acquired following the insonation to detect the hyperechoic bubble cloud. Phantom samples were sectioned and stained to delineate the liquefaction zone. Correlation between passive cavitation and plane wave B-mode images and the liquefaction zone was assessed using receiver operating characteristic (ROC) curve analysis. Liquefaction of the phantom was observed for all the insonation conditions. The area under the ROC (0.94 versus 0.82), accuracy (0.90 versus 0.83), and sensitivity (0.81 versus 0.49) was greater for passive cavitation images relative to B-mode images ( ${p} 〈 0.05$ ) along the azimuth of the liquefaction zone. The specificity was greater than 0.9 for both imaging modalities. These results demonstrate a stronger correlation between histotripsy-induced liquefaction and passive cavitation imaging compared with the plane wave B-mode imaging, albeit with limited passive cavitation image range resolution.

Description: Accurate identification of the needle target is crucial for effective epidural anesthesia. Currently, epidural needle placement is administered by a manual technique, relying on the sense of feel, which has a significant failure rate. Moreover, misleading the needle may lead to inadequate anesthesia, post dural puncture headaches, and other potential complications. Ultrasound offers guidance to the physician for identification of the needle target, but accurate interpretation and localization remain challenges. A hybrid machine learning system is proposed to automatically localize the needle target for epidural needle placement in ultrasound images of the spine. In particular, a deep network architecture along with a feature augmentation technique is proposed for automatic identification of the anatomical landmarks of the epidural space in ultrasound images. Experimental results of the target localization on planes of 3-D as well as 2-D images have been compared against an expert sonographer. When compared with the expert annotations, the average lateral and vertical errors on the planes of 3-D test data were 1 and 0.4 mm, respectively. On 2-D test data set, an average lateral error of 1.7 mm and vertical error of 0.8 mm were acquired.

Description: We present a comparative study for discriminative anatomy detection in high dimensional neuroimaging data. While most studies solve this problem using mass univariate approaches, recent works show better accuracy and variable selection using a sparse classification model. Two types of image-based regularization methods have been proposed in the literature based on either a Graph Net (GN) model or a total variation (TV) model. These studies showed increased classification accuracy and interpretability of results when using image-based regularization, but did not look at the accuracy and quality of the recovered significant regions. In this paper, we theoretically prove bounds on the recovered sparse coefficients and the corresponding selected image regions in four models (two based on GN penalty and two based on TV penalty). Practically, we confirm the theoretical findings by measuring the accuracy of selected regions compared with ground truth on simulated data. We also evaluate the stability of recovered regions over cross-validation folds using real MRI data. Our findings show that the TV penalty is superior to the GN model. In addition, we showed that adding an l 2 penalty improves the accuracy of estimated coefficients and selected significant regions for the both types of models.

Description: Similarity measure is a main core of image registration algorithms. Spatially varying intensity distortion is an important challenge, which affects the performance of similarity measures. Correlation among the pixels is the main characteristic of this distortion. Similarity measures such as sum-of-squared-differences (SSD) and mutual information ignore this correlation; hence, perfect registration cannot be achieved in the presence of this distortion. In this paper, we model this correlation with the aid of the low rank matrix theory. Based on this model, we compensate this distortion analytically and introduce rank-regularized SSD (RRSSD). This new similarity measure is a modified SSD based on singular values of difference image in mono-modal imaging. In fact, image registration and distortion correction are performed simultaneously in the proposed model. Based on our experiments, the RRSSD similarity measure achieves clinically acceptable registration results, and outperforms other state-of-the-art similarity measures, such as the well-known method of residual complexity.

Description: By exploiting cross-information among multiple imaging data, multimodal fusion has often been used to better understand brain diseases. However, most current fusion approaches are blind, without adopting any prior information. There is increasing interest to uncover the neurocognitive mapping of specific clinical measurements on enriched brain imaging data; hence, a supervised, goal-directed model that employs prior information as a reference to guide multimodal data fusion is much needed and becomes a natural option. Here, we proposed a fusion with reference model called “multi-site canonical correlation analysis with reference + joint-independent component analysis” (MCCAR+jICA), which can precisely identify co-varying multimodal imaging patterns closely related to the reference, such as cognitive scores. In a three-way fusion simulation, the proposed method was compared with its alternatives on multiple facets; MCCAR+jICA outperforms others with higher estimation precision and high accuracy on identifying a target component with the right correspondence. In human imaging data, working memory performance was utilized as a reference to investigate the co-varying working memory-associated brain patterns among three modalities and how they are impaired in schizophrenia. Two independent cohorts (294 and 83 subjects respectively) were used. Similar brain maps were identified between the two cohorts along with substantial overlaps in the central executive network in fMRI, salience network in sMRI, and major white matter tracts in dMRI. These regions have been linked with working memory deficits in schizophrenia in multiple reports and MCCAR+jICA further verified them in a repeatable, joint manner, demonstrating the ability of the proposed method to identify potential neuromarkers for mental disorders.

Description: Features of high-risk coronary artery plaques prone to major adverse cardiac events (MACE) were identified by intravascular ultrasound (IVUS) virtual histology (VH). These plaque features are: thin-cap fibroatheroma (TCFA), plaque burden PB ≥ 70%, or minimal luminal area MLA ≤ 4 mm 2 . Identification of arterial locations likely to later develop such high-risk plaques may help prevent MACE. We report a machine learning method for prediction of future high-risk coronary plaque locations and types in patients under statin therapy. Sixty-one patients with stable angina on statin therapy underwent baseline and one-year follow-up VH-IVUS non-culprit vessel examinations followed by quantitative image analysis. For each segmented and registered VH-IVUS frame pair ( ${n} =6341$ ), location-specific ( $approx 0.5$ mm) vascular features and demographic information at baseline were identified. Seven independent support vector machine classifiers with seven different feature subsets were trained to predict high-risk plaque types one year later. A leave-one-patient-out cross-validation was used to evaluate the prediction power of different feature subsets. The experimental results showed that our machine learning method predicted future TCFA with correctness of 85.9%, 81.7%, and 77.0% (G-mean) for baseline plaque phenotypes of TCFA, thick-cap fibroatheroma, and non-fibroatheroma, respectively. For predicting PB ≥ 70%, correctness was 80.8% for baseline PB ≥ 70% and 85.6% for 50% ≤ PB < 70%. Accuracy of predicted MLA ≤- 4 mm 2 was 81.6% for baseline MLA ≤ 4 mm 2 and 80.2% for 4 mm 2 < MLA ≤ 6 mm 2 . Location-specific prediction of future high-risk coronary artery plaques is feasible through machine learning using focal vascular features and demographic variables. Our approach outperforms previously reported results and shows the importance of local factors on high-risk coronary artery plaque development.

Description: We present a direct (noniterative) algorithm for 1-D quadratic data fitting with neighboring intensity differences penalized by the Huber function. Applications of such an algorithm include 1-D processing of medical signals, such as smoothing of tissue time concentration curves in kinetic data analysis or sinogram preprocessing, and using it as a subproblem solver for 2-D or 3-D image restoration and reconstruction. dynamic programming was used to develop the direct algorithm. The problem was reformulated as a sequence of univariate optimization problems, for ${k} =textsf {1}, ldots , {N}$ , where ${N}$ is the number of data points. The solution to the univariate problem at index ${k}$ is parameterized by the solution at ${k}+textsf {1}$ , except at ${k}={N}$ . Solving the univariate optimization problem at ${k}={N}$ yields the solution to each problem in the sequence using back-tracking. Computational issues and memory cost are discussed in detail. Two numerical studies, tissue concentration curve smoothing and sinogram preprocessing for image reconstruction, are used to validate the direct algorithm and illustrate its practical applications. In the example of 1-D curve smoothing, the efficiency of the direct algorithm is compared with four iterative methods: the iterative coordinate descent, Nesterov’s accelerated gradient descent algorithm, FISTA, and an off-the-shelf second order method. The first two methods were applied to the primal problem, the others to the dual problem. The comparisons show that the direct - lgorithm outperforms all other methods by a significant factor, which rapidly grows with the curvature of the Huber function. The second example, sinogram preprocessing, showed that robustness and speed of the direct algorithm are maintained over a wide range of signal variations, and that noise and streaking artifacts could be reduced with almost no increase in computation time. We also outline how the proposed 1-D solver can be used for imaging applications.

Description: The analysis of the pure motion of subnuclear structures without influence of the cell nucleus motion and deformation is essential in live cell imaging. In this paper, we propose a 2-D contour-based image registration approach for compensation of nucleus motion and deformation in fluorescence microscopy time-lapse sequences. The proposed approach extends our previous approach, which uses a static elasticity model to register cell images. Compared with that scheme, the new approach employs a dynamic elasticity model for the forward simulation of nucleus motion and deformation based on the motion of its contours. The contour matching process is embedded as a constraint into the system of equations describing the elastic behavior of the nucleus. This results in better performance in terms of the registration accuracy. Our approach was successfully applied to real live cell microscopy image sequences of different types of cells including image data that was specifically designed and acquired for evaluation of cell image registration methods. An experimental comparison with the existing contour-based registration methods and an intensity-based registration method has been performed. We also studied the dependence of the results on the choice of method parameters.

Description: We present a novel method to segment instances of glandular structures from colon histopathology images. We use a structure learning approach which represents local spatial configurations of class labels, capturing structural information normally ignored by sliding-window methods. This allows us to reveal different spatial structures of pixel labels (e.g., locations between adjacent glands, or far from glands), and to identify correctly neighboring glandular structures as separate instances. Exemplars of label structures are obtained via clustering and used to train support vector machine classifiers. The label structures predicted are then combined and post-processed to obtain segmentation maps. We combine hand-crafted, multi-scale image features with features computed by a deep convolutional network trained to map images to segmentation maps. We evaluate the proposed method on the public domain GlaS data set, which allows extensive comparisons with recent, alternative methods. Using the GlaS contest protocol, our method achieves the overall best performance.

Description: An on-demand long-lived ultrasound contrast agent that can be activated with single pulse stimulated imaging (SPSI) has been developed using hard shell liquid perfluoropentane filled silica 500-nm nanoparticles for tumor ultrasound imaging. SPSI was tested on LnCAP prostate tumor models in mice; tumor localization was observed after intravenous (IV) injection of the contrast agent. Consistent with enhanced permeability and retention, the silica nanoparticles displayed an extended imaging lifetime of 3.3±1 days (mean±standard deviation). With added tumor specific folate functionalization, the useful lifetime was extended to 12 ± 2 days; in contrast to ligand-based tumor targeting, the effect of the ligands in this application is enhanced nanoparticle retention by the tumor. This paper demonstrates for the first time that IV injected functionalized silica contrast agents can be imaged with an in vivo lifetime ~500 times longer than current microbubble-based contrast agents. Such functionalized long-lived contrast agents may lead to new applications in tumor monitoring and therapy.

Description: Functional magnetic resonance imaging (fMRI) provides a window on the human brain at work. Spontaneous brain activity measured during resting-state has already provided many insights into brain function. In particular, recent interest in dynamic interactions between brain regions has increased the need for more advanced modeling tools. Here, we deploy a recent fMRI deconvolution technique to express resting-state temporal fluctuations as a combination of large-scale functional network activity profiles. Then, building upon a novel sparse coupled hidden Markov model (SCHMM) framework, we parameterised their temporal evolution as a mix between intrinsic dynamics, and a restricted set of cross-network modulatory couplings extracted in data-driven manner. We demonstrate and validate the method on simulated data, for which we observed that the SCHMM could accurately estimate network dynamics, revealing more precise insights about direct network-to-network modulatory influences than with conventional correlational methods. On experimental resting-state fMRI data, we unraveled a set of reproducible cross-network couplings across two independent datasets. Our framework opens new perspectives for capturing complex temporal dynamics and their changes in health and disease.

Description: The integration of compressed sensing and parallel imaging (CS-PI) has shown an increased popularity in recent years to accelerate magnetic resonance (MR) imaging. Among them, calibration-free techniques have presented encouraging performances due to its capability in robustly handling the sensitivity information. Unfortunately, existing calibration-free methods have only explored joint-sparsity with direct analysis transform projections. To further exploit joint-sparsity and improve reconstruction accuracy, this paper proposes to Learn joINt-sparse coDes for caliBration-free parallEl mR imaGing (LINDBERG) by modeling the parallel MR imaging problem as an $ell _{textsf {2}}$ – $ell _{F}$ – $ell _{textsf {2},textsf {1}}$ minimization objective with an $ell _{textsf {2}}$ norm constraining data fidelity, Frobenius norm enforcing sparse representation error and the $ell _{textsf {2},textsf {1}}$ mixed norm triggering joint sparsity across multichannels. A corresponding algorithm has been developed to alternatively update the sparse representation, sensitivity encoded images and K-space data. Then, the final image is produced as the square root of sum of squares of all channel images. Experimental results on both physical phantom and in vivo data sets show that the proposed method is comparable and even superior to state-of-the-art CS-PI reconstruction approaches. Specifically, LINDBERG has presented strong capability in suppressing noise and artifacts while reconstructing MR images from highly undersampled multichannel measurements.

Description: This paper presents a method for automatically calibrating and assessing the calibration quality of an externally tracked 2-D ultrasound (US) probe by scanning arbitrary, natural tissues, as opposed a specialized calibration phantom as is the typical practice. A generative topic model quantifies the posterior probability of calibration parameters conditioned on local 2-D image features arising from a generic underlying substrate. Auto-calibration is achieved by identifying the maximum a-posteriori image-to-probe transform, and calibration quality is assessed online in terms of the posterior probability of the current image-to-probe transform. Both are closely linked to the 3-D point reconstruction error (PRE) in aligning feature observations arising from the same underlying physical structure in different US images. The method is of practical importance in that it operates simply by scanning arbitrary textured echogenic structures, e.g., in-vivo tissues in the context of the US-guided procedures, without requiring specialized calibration procedures or equipment. Observed data take the form of local scale-invariant features that can be extracted and fit to the model in near real-time. Experiments demonstrate the method on a public data set of in vivo human brain scans of 14 unique subjects acquired in the context of neurosurgery. Online calibration assessment can be performed at approximately 3 Hz for the US images of $640times 480$ pixels. Auto-calibration achieves an internal mean PRE of 1.2 mm and a discrepancy of [2 mm, 6 mm] in comparison to the calibration via a standard phantom-based method.

Description: The use of appearance and shape priors in image segmentation is known to improve accuracy; however, existing techniques have several drawbacks. For instance, most active shape and appearance models require landmark points and assume unimodal shape and appearance distributions, and the level set representation does not support construction of local priors. In this paper, we present novel appearance and shape models for image segmentation based on a differentiable implicit parametric shape representation called a disjunctive normal shape model (DNSM). The DNSM is formed by the disjunction of polytopes, which themselves are formed by the conjunctions of half-spaces. The DNSM’s parametric nature allows the use of powerful local prior statistics, and its implicit nature removes the need to use landmarks and easily handles topological changes. In a Bayesian inference framework, we model arbitrary shape and appearance distributions using nonparametric density estimations, at any local scale. The proposed local shape prior results in accurate segmentation even when very few training shapes are available, because the method generates a rich set of shape variations by locally combining training samples. We demonstrate the performance of the framework by applying it to both 2-D and 3-D data sets with emphasis on biomedical image segmentation applications.

Description: This paper describes an automated method for registering 3-D models of metallic knee implants to single-plane radiographic images. We develop a multistage approach that identifies the correct pose by matching altered dilations of an edge-detected image with the silhouette of an implant model. The location of the similarity function’s minimum is found using a novel optimization routine that combines the Dividing Rectangles algorithm with properties of the registration metric. Depending on the implant type (tibial or femoral), this technique reliably converges under maximum displacements of approximately 25 to 55 millimeters for translation components and 25° to 55° for Euler angles. The method proves to be robust to noise from bones and soft tissue. After an initial guess for the first image in the sequence, subsequent frames can be automatically registered from the optimum pose in the previous image.

Description: Presents the farewell message from the founding Editor-in-Chief.

Description: One-way electromagnetic mode that is guided by the mechanism of total internal reflection (TIR) can be realized in terahertz regime. In the optical system consisting of a dielectric layer sandwiched between magnetized semiconductor and metal, the one-way TIR mode can be immune to backscattering at imperfections. This mode possesses a broad band when high-order TIR modes are suppressed in the relevant semiconductor bandgap. Furthermore, it is shown that compared with one-way surface magnetoplasmons, the one-way TIR mode can more effectively match with the fundamental mode of conventional optical waveguide.

Description: This paper presents a flexible 2.45-GHz wireless power harvesting wristband that generates a net dc output from a −24.3-dBm RF input. This is the lowest reported system sensitivity for systems comprising a rectenna and impedance-matching power management. A complete system has been implemented comprising: a fabric antenna, a rectifier on rigid substrate, a contactless electrical connection between rigid and flexible subsystems, and power electronics impedance matching. Various fabric and flexible materials are electrically characterized at 2.45 GHz using the two-line and the T-resonator methods. Selected materials are used to design an all-textile antenna, which demonstrates a radiation efficiency above 62% on a phantom irrespective of location, and a stable radiation pattern. The rectifier, designed on a rigid substrate, shows a best-in-class efficiency of 33.6% at −20 dBm. A reliable, efficient, and wideband contactless connection between the fabric antenna and the rectifier is created using broadside-coupled microstrip lines, with an insertion loss below 1 dB from 1.8 to over 10 GHz. A self-powered boost converter with a quiescent current of 150 nA matches the rectenna output with a matching efficiency above 95%. The maximum end-to-end efficiency is 28.7% at −7 dBm. The wristband harvester demonstrates net positive energy harvesting from −24.3 dBm, a 7.3-dB improvement on the state of the art.

Description: This paper presents an RF-powered transceiver for wireless sensor network applications. The circuit is composed of an RF energy harvesting system, implemented by means of a threshold-compensated multistage rectifier, power management unit, and phase-locked loop (PLL)-based RF front end. Initially, the PLL in closed-loop condition locks the voltage-controlled oscillator (VCO) to a multiple of the RF input frequency and allows frequency-shift keying (FSK) data recovery. Then, the PLL feedback loop is opened and the VCO signal is used to generate the uplink carrier, thus enabling active transmission without requiring external quartz for frequency reference. This approach overcomes the reader self-jamming drawback that greatly limits the operating range of backscattering-based RF-powered devices. Moreover, uplink and downlink operations are performed by exploiting a single carrier frequency according to a half-duplex communication scheme, which results in a low-complexity and low-cost wireless solution. The circuit was fabricated in a 130-nm CMOS technology and operates with a minimum input power as low as −18.8 dBm. It supports the FSK and ASK demodulation and OOK data transmission in the industrial scientific and medical band at 915 MHz.

Description: A W-band injection-locked frequency divider (ILFD) with low-power and wide locking range is presented in this paper. The operation frequency and locking range are enhanced by using split transformer-coupled oscillator. The optimum bias and the size of the injection transistor are chosen to achieve wider locking range without increasing chip area and dc power consumption. The proposed ILFD is implemented in 90-nm CMOS and exhibits 25.4% locking range from 75.1 to 99 GHz at an input power of 0 dBm without any tuning mechanism. The core dc power consumption is 2.45 mW with a supply voltage of 0.7 V and the core chip size is $0.13 times 0.2$ mm 2 .

Description: A fully tunable baseband ultra-wideband pulse generator realized with commercial off-the-shelf components is presented. It is made of high-speed logic gates and comparators, and it is compliant with the current-mode logic digital standard. The pulse emitted power and bandwidth are tunable with pulsewidth and amplitude variation, which shows high flexibility. This advantage simplifies the design of the downstream shaping network, as so to be compliant with international regulations. A differential output with very low jitter is demonstrated.

Description: We present a modulated ultrawideband backscatter calibration target (fiducial) intended for group delay calibration in large-aperture multitransceiver millimeter-wave imagers. The fiducial is designed to resemble a modulated point scatterer across the K-band (17.5–26.5 GHz). Multiple such fiducials may be used to mitigate thermal and mechanical drift across multiple transceivers comprising the imager. This approach allows tracking and removing both time-varying amplitude and phase drift in the RF hardware and associated cables. Backscatter modulation of the fiducial allows the system to separate the fiducial from the imaged scene and clutter in the environment. We show that the −10 dB beamwidth of the proposed fiducial is approximately 84° along the azimuth plane and 60° along the elevation plane. A proof of concept group delay calibration experiment is presented for a K-band laboratory setup, where a single fiducial and a metal plate target are placed in a scene together. After the backscatter-based calibration, the measured range error of the metal plate at a two-way slant distance of 70.54 cm is reduced to only 1.06 mm (0.15% position error).

Description: We propose and experimentally demonstrate a photonic technique for Fourier transformation of broadband optical spectrum and compression of time–bandwidth product (TBP) simultaneously. Conventionally, an optical spectrum could be Fourier transformed based on the so-called time-spectrum convolution technique with a linearly dispersive delay line. In this paper, a nonlinearly dispersive delay line is implemented by the convolution of an input optical spectrum in the spectral domain with a nonlinearly chirped temporal sinusoidal waveform in the time domain. By specially designing the chirp rate variation of the temporal waveform, an anamorphic Fourier transformation functionality is realized to compress the TBP of output waveform. The key feature of this paper is that it is the first time to our knowledge to carry out the Fourier transformation of an optical spectrum with TBP compression. In addition, since the dispersive delay line could be programmable with high resolution, this technique is adaptable for different optical spectra and realizable for a reconfigurable TBP compression ratio. Experimental results show that the TBP compression ratio is programmable from 1.6 to 3 by engineering the nonlinear dispersive delay line. After reconstructing the Fourier transform of optical spectrum from the output waveforms, the error rate of the recovered waveform is calculated quantitatively. Also, we discussed and proved the possibility to recover the input spectrum only with intensity information. This proposed method is promising to break the big data limitation of the conventional real-time optical spectrum Fourier transformation technique based on the TBP engineering for data compression.

Description: Public acceptability is at the heart of changing the energy system toward a more sustainable way of energy production and use. Without public acceptability and support for changes, a sustainable energy transition is unlikely to be viable. We argue that public acceptability is often addressed too late and should be incorporated into the planning process from the start. Moreover, engineers, policy makers, and project developers tend to misjudge the complexity and causes of public resistance, trying to find the magic bullet to "solve" the lack of public acceptability. Such attempts are likely to be ineffective, or even counterproductive, if they fail to address people's key concerns surrounding energy projects. There is not a one-size-fits-all solution: public acceptability is a dynamic process that depends on the context, the specific project at stake, and the parties involved.

Description: This paper is devoted to the analysis of electromagnetic field excited by a charge moving in a circular waveguide, which consists of two semi-infinite parts. The charge moves with a constant velocity along the waveguide axis from the partially dielectric section into the homogeneous one. It is assumed that Cherenkov radiation is generated in the bilayer section. The total field is represented as a sum of a known forced field that is the field of the charge in the infinite regular waveguide and a free field resulting from the presence of the transverse boundary. The infinite system of algebraic equations for amplitudes of the free-field modes is derived. The further analysis is conducted using numerical calculations. Special attention is given to the study of the so-called Cherenkov-transition radiation (CTR) within the homogeneous part of the waveguide volume. Typical distributions of CTR over frequencies and modes are presented for the case when the channel and the homogeneous area are free of medium. Analytical results obtained for the point charge are generalized for the charged bunch with an arbitrary profile and verified using direct simulations for the case of Gaussian bunch.

Description: A new artificial material single layer (AMSL) model is presented to solve shielding problem. The field penetration through the conductive shield is described by lossy transmission line equations. The resulting equations are used to numerically synthetize an equivalent material for the shield region having the same geometrical configuration of the original shield, but different specific constants. The AMSL method is very accurate and highly efficient since it allows to discretizing the shield region using only a single layer of finite elements avoiding the fine discretization required by the finite-element method (FEM) to model the skin effect. The most relevant aspect of the proposed procedure is that the AMSL method can be easily implemented in FEM-based commercial software tools.

Description: Performing a stability analysis during the design of any electronic circuit is critical to guarantee its correct operation. A closed-loop stability analysis can be performed by analyzing the impedance presented by the circuit at a well-chosen node without internal access to the simulator. If any of the poles of this impedance lie in the complex right half-plane, the circuit is unstable. The classic way to detect unstable poles is to fit a rational model on the impedance. In this paper, a projection-based method is proposed which splits the impedance into a stable and an unstable part by projecting on an orthogonal basis of stable and unstable functions. When the unstable part lies significantly above the interpolation error of the method, the circuit is considered unstable. Working with a projection provides one, at small cost, with a first appraisal of the unstable part of the system. Both small-signal and large-signal stability analysis can be performed with this projection-based method. In the small-signal case, a low-order rational approximation can be fit on the unstable part to find the location of the unstable poles.

Description: This paper presents a mechanically assisted microwave drill (MWD) capable of drilling 26-cm-deep 12-mm-diameter holes in concrete. This record significantly extends the inherent $lambda $ /4-depth capability (~1.5 cm at 2.45 GHz) of the basic MWD scheme. Compared with conventional mechanical drills, this MWD is characterized by a relatively silent and vibration-free operation, but its drilling speed is yet slower than 1 cm/min. This paper reviews the fundamental MWD mechanism (utilizing localized microwave heating and thermal-runaway instability), and extends it for deeper holes by also using the coaxial applicator as a slowly rotating hollow reamer to remove the debris. The MWD prototype is introduced, including its adaptive impedance matching and remote-operation features, and its experimental results are presented. Theoretical and practical MWD aspects are discussed, and potential developments are indicated (e.g., for faster drilling and iron-rebar cutting). The present MWD performance can be useful for specific applications which critically require silent drilling operations in concrete.

Description: Modern reservoir management in oil and gas industry relies on accurate water fraction measurement which is produced as a by-product with oil. This paper presents a novel and contactless water fraction (also known as water-cut) measurement technique which is independent of geometric distribution of oil and water inside the pipe. The sensor is based on a modified T-resonator implemented directly on the pipe’s outer surface and whose resonance frequency decreases by increasing the water content in oil. The E-fields have been made to rotate and distribute well inside the pipe, despite having narrow and curved ground plane. It makes the sensor’s reading dependent only on the water fraction and not on the mixture distribution inside the pipe. That is why, the presented design does not require any flow conditioner to homogenize the oil/water mixture unlike many commercial water-cut (WC) sensors. The presented sensor has been realized by using extremely low-cost methods of screen printing and reusable 3-D printed mask. Complete characterization of the proposed WC sensor, both in horizontal and vertical orientations, has been carried out in an industrial flow loop. Excellent repeatability of the sensor’s response has been observed in “dispersed bubble” as well as in “stratified wavy” flow regimes. The performance test of the sensor confirms that the water fraction measurement is independent of the flow pattern, flow rate or orientation. The measured performance results of the sensor show full range accuracy of ±2%–3% while tested under random orientations and wide range of flow rates.

Description: A simple design for an orthomode transducer (OMT) is proposed for low-power antenna applications, such as receiver antennas as well as laboratory testing antennas. The design exploits detuning pins to enable enlarging the higher order mode-free bandwidth in an asymmetric configuration without compromising the port isolation. The design guidelines are presented for a scalable design. Moreover, the design is optimized to utilize all the single-mode operation bandwidth of the circular waveguide, covering the satellite communications band in North America (i.e., from 11.7 to 14.2 GHz). The presented OMT features a port coupling level below −34 dB. The measurement results are in a very good agreement with the full-wave analysis simulations.

Description: Power combiners are in general complex to manufacture and do not show a compact structure when more than two output ports are needed. To overcome these problems, the design of a five-way Bagley polygon in rectangular waveguide is presented. The proposed geometry is simple, suitable for an efficient optimization, and allows its fabrication by milling. A five-way Ku-band $E$ -plane rectangular waveguide Bagley polygon for a 17% fractional bandwidth is designed, manufactured, and measured. The measured results show return loss better than 28 dB and amplitude and phase imbalances below ±0.2 dB and ±5°, respectively, which, along with the waveguide low losses, leads to a 98% efficiency as power combiner.

Description: The design and performance of a broadband and low-reflectivity millimeter-wave vacuum window for rectangular hollow waveguides are presented. A reflectivity below −15 dB is achieved over almost the full ${W}$ -band. The vacuum window is sufficiently compact, so that two separate channels fit into a single ConFlat CF-35 vacuum flange. The proposed vacuum window utilizes a well-known circuit concept based on two-quadrature hybrid couplers together with two identical vacuum barriers (similar to a balanced amplifier). Due to the dielectric discontinuity at the vacuum barrier, a part of the incident wave is transmitted and another part is reflected. A hybrid lattice network recombines the transmitted signals and reroutes all reflected power to absorbers. The proposed low-reflectivity vacuum window has been fabricated in the WR10 waveguide technology. Broadband branch-guide couplers enable an operational frequency range of 75–105 GHz. Ultrahigh vacuum compatibility is verified by a helium leak rate test, and electrical measurements show good agreement with full-wave simulations.

Description: This paper introduces a novel compact ultralightweight multiband RF energy harvester fabricated on a paper substrate. The proposed rectenna is designed to operate in all recently released LTE bands (range 0.79–0.96 GHz; 1.71–2.17 GHz; and 2.5–2.69 GHz). High compactness and ease of integration between antenna and rectifier are achieved by using a topology of nested annular slots. The proposed rectifier features an RF-to-dc conversion efficiency in the range of 5%–16% for an available input power of −20 dBm in all bands of interest, which increases up to 11%–30% at −15 dBm. The rectenna has been finally tested both in laboratory and in realistic scenarios featuring a superior performance to other state-of-the-art RF harvesters on flexible substrates.

Description: This paper presents a rotatable cyclic Vernier digital-to-time converter (DTC) with 1.8 ps timing resolution on an 80 ns time scale. The proposed DTC features high timing resolution, and can be utilized in beam-steering arrays, which is infeasible for ordinary Vernier DTCs. The proposed DTC was implemented within a passive time-equivalent direct-sampling ultra-wideband impulse-radio radar system and was fabricated in 65 nm CMOS technology. This radar system is capable of quantizing direct-sampled impulse waveforms to provide full degrees of freedom for backend digital signal processing. The measured differential nonlinearity/integral nonlinearity of the DTC was +4.6/−3 and 12.4/−9.4 where the LSB was 1.8 ps, and the total power consumption was 133 mW. Also, a new method for localization between wireless sensor nodes of equivalent-time direct-sampling radar is presented in this paper; this method can theoretically achieve resolution as high as that of regular radar.

Description: Imaging of subcutaneous vasculature is of great interest for biometric security and point-of-care medicine. We investigate the feasibility of microwave-induced thermoacoustic (TA) tomography as a safe, compact, low-power, and cost-effective imaging technique for subcutaneous vasculature by means of application-specific design of near-field, radio frequency (RF) applicators. Using commercial transducers, we demonstrate proof-of-concept TA imaging of synthetic phantoms, plant vasculature, and earthworm blood vessels with only 50 W of peak power, or 42 mW average power, at 300 $mu text{m}$ resolution. The proposed RF applicator design enabled uniform, orientation-independent illumination of vasculature phantoms with only 10% variation. Finally, we show that the benefits of microwave contrast make possible the distinction of actual blood vessels, in an earthworm, from surrounding tissue within a modest receiver dynamic range of 40 dB.

Description: This paper presents a compact T-type switch that involves three different operational states providing high flexibility in signal routing. Two of the states are between adjacent ports, while the other is a crossover state. T-type switches are mainly used as building blocks of redundancy matrices for satellite communications systems, although mobile applications also take advantage of switching devices. The proposed structure uses p-i-n diodes located in specific points to control each state with a specific bias dc voltage, creating open and short circuits. The symmetry of the structure allows even–odd mode analysis in order to obtain the design equations. To validate the concept, a compact microstrip T-type switch is fabricated and measured. The resulting device shows a good performance in terms of transmission and isolation for each state, in agreement with the simulations. The switch exhibits a band-pass response for the crossover state, while low-pass and high-pass responses result for the other two states.

Description: In this paper, a tangential network transmission theory is established for the reflective metasurface composed of periodic subwavelength metallic elements and a perfect electrical conductor (PEC)-backed substrate. The theory is divided into two parts. The first part shows that the oblique incidence can be handled the same way as a normal incidence for a PEC-backed substrate in terms of tangential components of electric fields and a normal wave vector. Therefore, the network transmission theory is extended from the PEC-backed substrate to the reflective metasurface, whose total tangential reflection matrix depends on the induction matrix of the metallic elements in the air–substrate interface. The second part deals with the conversion of the induction matrices of different metallic elements into equivalent circuits, whose electrical parameters can be theoretically calculated or extracted from numerical simulations. Based on the obtained electrical parameters, the theory can be used to analyze or design reflective metasurfaces. Finally, the theory is verified by a metasurface, which is composed of periodic double-L shaped elements. The analytical results agree with the simulated ones for arbitrary substrate and incidence angle. The measured results further validate the proposed theory.

Description: Providing clean, safe, reliable, and affordable energy for people everywhere will require converting to an energy system in which the use of fossil fuels is minimal. A sustainable energy transition means substantial changes in technology and the engagement of the engineering community. But it will also mean changes in behavior and policies and, thus, will require the engagement of the social science community. The choices, preferences, and behaviors of individuals and households are major direct influences on energy demand, and they also shape the acceptability and effectiveness of technologies, strategies, and policies to bring about a sustainable energy transition. A successful transition to a more sustainable energy system will require a wide range of sustainable actions by diverse people across the globe.

Description: To combat climate change, the Intergovernmental Panel for Climate Change (IPCC) calculated that greenhouse gas emissions in the energy domain should be reduced by 90%, compared to 2010 emissions, between the years 2040 and 2070. In Europe, residential households consume about a quarter of total energy used (excluding the energy that is embodied in products). To contribute to the carbon emission reduction targets set by the IPCC , households need to reduce their fossilenergy use.

Description: A monomaterial-based resonator structure is proposed here, which can replace the multilayer-based narrowband transmission filter. This new concept of introducing the effect of multilayered structures of different materials into a single material is based on etching out repeatable structures of two different dimensions on the same material. As the etched-out repeatable structures are of different dimensions, it is possible to obtain periodic layers of two different-effective refractive indices. This type of monomaterial-based optical filters avoids the challenges generally faced while fabricating multilayer structures of different heterogeneous materials having different refractive indices. The dependence of the filter action on the number of bilayers of two different-effective refractive-index materials formed by etching and on the cavity region thicknesses is studied. Although the study is done mainly on lithium niobate on insulator, but it is seen that similar effects occur for materials of varying refractive indices.

Description: From about 1885 to 1915, the most common means of lighting streets was the use of arc lamps. These lamps and the systems by which they were supplied power were very technologically sophisticated. These were the first electrical distribution systems. The manufacturing companies that made the equipment for arc lighting went on to be the companies that launched the so-called electrical age.

Description: This paper presents the theoretical and experimental study of a novel noncontact heart-beat signal modeling and estimation algorithm using a compact 2.4-GHz Doppler radar. The proposed technique is able to accurately reconstruct the heart-beat signal and generates heart rate variability indices at a distance of 1.5 m away from the human body. The feasibility of the proposed approach is validated by obtaining data from eight human subjects and comparing them with photoplethysmography (PPG) measurements. A Gaussian pulse train model is suggested for the heart-beat signal along with a modified-and-combined autocorrelation and frequency-time phase regression technique for high-accuracy detection of the human heart-beat rate. The proposed method is accurate, robust, and simple, and demonstrates an average heart-beat detection accuracy of more than 90% at a distance of 1.5 m away from the subjects. In addition, the average beat-to-beat time intervals extracted from the proposed model and signal reconstruction method show less than 2% error compared to PPG measurements. Bland–Altman analysis further validated the accuracy of the proposed approach in comparison with reference data.

Description: A new phase retrieval technique in digital holographic microscopy (DHM) with three defocused holograms is proposed. Given the defocusing distance, the phase distributions of tested specimen can be reconstructed with a simple algebraic equation. We have deduced this equation in detail. To avoid the manual operation, the defocused holograms can be flexibly and precisely obtained by introducing an electronically tunable lens based 4f system. This method is suitable for an on-axis hologram as well as the off-axis one but avoids the requirements for not only the iterative process, complex spectrum selection in off-axis DHM or additional phase-shifting devices in on-axis DHM but also the assumption of tested specimen or previous knowledge of the system. A series of simulations and the experimental results of the microlens array and water drop demonstrate the feasibility and effectiveness of the proposed method.

Description: Binocular stereo vision (BSV) system has been widely used in various fields, such as intelligent manufacture, smart robot, and so on. However, the location accuracy of the current BSV still cannot fully satisfy industry requirements due to lack of a parameters optimization BSV system. In this paper, a high accuracy BSV system is proposed. This is achieved through analyzing the seven parameters of the BSV system, which are classified into two groups: system structure parameters (SSPs) and camera calibration parameters (CCPs). For the SSPs, an improved analysis model is designed to expose the possible errors caused by three parameters. Furthermore, a new correlation model among them is also proposed to analyze the errors caused by their correlation. On the other hand, for the CCPs, the orthogonal experiment model is employed for selecting the optimal combination of the four calibration parameters. Meanwhile, the weight among the four parameters is also analyzed for reducing errors. Finally, the effectiveness of our proposed method is demonstrated by a large number of experiments. It gives a useful reference to the BSV system used in applied optics research and application fields.

Description: A discrete-mode laser diode, fabricated in the In0.6Ga0.4P/AlGaInP multiple quantum well system, emitting a single mode at $lambda =689$ nm is reported. The laser has an ex-facet output power >10 mW at 30 °C and operates mode hop free in the temperature range 0 °C to 50 °C.

Description: We designed a terahertz bandpass filter based on double-layer frequency selective surface. Details of the proposed terahertz wave filter design and of the related parametric analysis are presented and discussed. The proposed terahertz filter was fabricated by laser technology. The transmission spectrum was characterized by terahertz time-domain spectroscopy. The results show that the center frequency of the terahertz filter is about 1 THz with 3-dB bandwidth of 400 GHz.

Description: Single longitudinal mode emission of laterally coupled distributed-feedback (LC-DFB) laser diodes (LDs) based on InGaN/GaN multiquantum-well structures containing 10th-order surface Bragg gratings with V-shaped grooves is demonstrated. The gratings were fabricated alongside a 2- $mu text{m}$ -wide contact stripe by i-line stepper lithography and inductively coupled plasma etching. A single peak emission at 404.6 nm with a full-width at half-maximum of 0.04 nm was achieved at an output power of about 46 mW under pulsed laser operation. The shift of the lasing wavelength of LC-DFB LDs in the temperature range from 22 °C to 45 °C was around three times smaller than that of comparable ridge waveguide Fabry–Pérot LDs.

Description: We experimentally demonstrate a fiber-based reconfigurable system for programming the envelope of high-speed optical pulse train by using fractional-rate multilevel amplitude modulation. Amplitude-modulated optical pulse trains undergo the discrete Fourier transform (DFT) realized by the temporal Talbot effect in a dispersive fiber. Consequently, rate-multiplied optical pulse trains with programmable envelopes can be achieved. In this letter, we report experimental synthesis of ~80-GHz optical pulse trains with expectant binary patterns, parabolic, square, and triangular envelopes. We also consider practical implementation issues and numerically analyze the influence from the deviation of modulation coefficients and finite extinction ratio of the Mach–Zehnder modulator on the generated pulses.

Description: A novel approach for measuring the microwave Doppler frequency shift (DFS) based on a dual-drive Mach–Zehnder modulator (DDMZM) is proposed and demonstrated. The value and direction of the DFS can be simultaneously measured with high precision by using a reference signal. In the DDMZM, the transmitted signal and reference signal are applied to one radio frequency (RF) port, while the echo signal is applied to the other RF port. Then, the generated optical signals are sent to a low-speed photodetecter, and the beat frequency between the transmitted and echo signals is equal to the value of DFS, while the direction of DFS can be distinguished by comparing the two beat frequencies generated by the transmitted signal with reference signal and the echo signal with reference signal, respectively. The DFS from −100 to +100 kHz at the carrier frequency of 10, 14, and 18 GHz is successfully measured, and the maximal error is less than 1.0 Hz.

Description: We demonstrate that using a broadband, first order, and coherent pump laser enables effective and efficient forward-pumped distributed Raman amplification for long-haul transmission systems, thanks to the simultaneous suppression of ASE noise and RIN-related penalty. We show in both experiments and simulation that this scheme extends the reach of $10times120$ Gb/s DP-QPSK WDM transmission by a minimum of 50%, compared with low RIN Bi-doped fibre laser and other commercially available pump lasers. Moreover, it requires very low forward pump power, and maintains uniform/symmetric signal power distribution which allows effective nonlinearity compensation.

Description: Wire-mesh sensors produce 3-D data of void fraction distribution at high resolution thus being an appropriate tool to investigate two-phase gas-liquid flows. Slug flow is typically found in petroleum production lines. This type of flow is characterized by the intermittent occurrence of gas bubbles and liquid slugs along the pipe. An important issue of these flows is the existence of a variety of regimes, depending on the flow rates of gas and liquid. The quantitative and qualitative information about shapes of the bubble nose and tail allows to study and to model the flow characteristics in order to increase safety and efficiency of oil production operations. In this paper, we describe two methods to estimate typical bubble shape from wire-mesh sensor data, which are based on ensemble mean and median approaches. Results from a set of two-phase flow experiments in inclined tubes, show that both approaches produce similar estimations, however since median is a type of robust estimator, contours of bubbles are better defined. 3-D images of typical bubbles, for eight different operational conditions, were generated and reveal some details about bubble shape. In addition, the bubble identification was validated by measuring the gas flow rate in comparison with reference instrumentation.

Description: This paper gives a solution to solve the interference problem of electronic nose (e-nose), which is ill-posed due to the uncertainty and unpredictability of its instable behavior. Traditional methods for interference suppression are component correction frameworks, which are laborious or little efficient. With interference (especially background interference and sensor drift), the distribution of test data obtained in practical application is different from that of the previous training data. From the viewpoint of machine learning, a novel domain correction and adaptive extreme learning machines (DC-AELM) framework with transferring capability is proposed to solve the serious interference problem in e-nose. The framework consists of two parts: 1) DC, which makes the distributions of two domains close and 2) AELM, which realizes the knowledge transfer at the decision level and makes the robustness of the prediction model improved. This method is motivated by the idea of transfer learning, especially from the perspective of domain correction and decision-making, to realize the knowledge transfer for interference suppression. A background interference data set obtained by our designed e-nose and a public benchmark sensor drift data set are used to verify the effectiveness of the proposed DC-AELM method.

Description: Non-contact displacement measurement based on the phase-based microwave interferometry technology has attracted growing interest in recent years. In this paper, aiming to exploit the frequency-modulated continuous wave (FMCW) radar-based vibration monitoring technique, the principle and detailed procedure for extracting the displacement time series of vibration movement are illustrated. The approximate maximum likelihood approach is proposed to extract the phase history of beat signals across multiple sweep periods. Moreover, the measurement accuracy of vibration displacement extraction and several practical issues of this technique are evaluated and concerned. Both simulated and experimental validations are provided to show the effectiveness and robustness of the proposed method and approach.

Description: Compressed sensing (CS) for sparse backscattering field recovery from very limited measurements has received increasing attention among the radar imaging community. The chirp (i.e., linear frequency modulated) waveform, benefiting from a large time-bandwidth product, is widely utilized in imaging radars, such as synthetic aperture radars (SARs) and inverse SARs (ISARs). In this paper, the influence of sub-Nyquist sampling jamming on ISAR with chirp waveform is investigated, where the CS-based dechirping (CS-D) algorithm is applied to achieve range compression of the under-sampled jamming signals. The jamming signals, formed by the intercepted radar signals under the sub-Nyquist sampling theorem and scattered by the moving targets, are collected by ISAR to form a (2-D) array and the azimuth compression is done via conventional Fourier transform. The main novelty of this framework is twofold: 1) the CS-D range compression of the under-sampled jamming signals is characterized and 2) the potential of sub-Nyquist sampling jamming is demonstrated against ISAR with the CS-D range compression. Simulated trials and real data of a Yak-42 plane are used to validate the correctness of the analyses and finally, the well-focused false-target images greatly support the effectiveness of the sub-Nyquist sampling jamming idea in the countermeasures of chirp-ISAR with the CS-D range compression.

Description: We developed a gyroscope with less than 1-deg/h bias instability variation in a temperature range from −40 °C to 125 °C while performing around 4-deg/h bias instability. This stability was achieved by using the stable frequency separation between the drive and sense modes of a Coriolis vibratory gyroscope. To achieve this stability, the mechanical part was designed with a one-sided open frame to mitigate the variation of resonant frequencies caused by thermal stress. At the circuit level, we implemented a self-clocking architecture with a bandpass $Sigma -Delta $ analog-to-digital converter to maintain low quantization noise level over the operational temperature range. The fabricated gyroscope demonstrated a 2-Hz variation of frequency separation for an operational frequency of 18.5 kHz in the operational temperature range. At a system level, a bias instability variation of 0.9 deg/h in the temperature range while performing bias instability less than 4.21 deg/h was demonstrated. This low-noise variation is potentially beneficial for applications requiring a Kalman filter, such as GPS-denied navigation systems, that demands a precise and predetermined noise property.

Description: In this paper, we propose a generalized co-prime multiple-input multiple-output (MIMO) configuration for direction of arrival estimation. Compared with the conventional co-prime MIMO radar that requires prototype co-prime arrays for transmitter and receiver, the proposed configuration enlarges the inter-element spacing of transmitter with an integer expansion factor. By vectorizing the sample covariance matrix, the generalized sum and difference coarray (GSDC) concept is defined for exploiting the advantages of proposed configuration. The analytical expressions for the expansion factor, the maximum consecutive lags, and the number of unique lags are derived carefully. It is verified that GSDC can obtain more degrees of freedom (DOFs) with the increase of expansion factor. Specifically, with $mathcal {O}(M+N)$ sensors, GSDC can provide $mathcal {O}(M^{2}N^{2})$ DOFs, whereas the conventional one only has $mathcal {O}(MN)$ DOFs. Simulation results demonstrate the usefulness of proposed configuration utilizing both spatial smoothing and sparse representation algorithms.

Description: The deployment of Wi-Fi fingerprint-based indoor positioning systems is severely hindered by the lack of an efficient and low-cost way to establish a signal fingerprint database. In this paper, we present a novel fingerprinting method, slide , that can collect fingerprints in a fast and accurate way. Slide uses a commodity flashlight and a smartphone to achieve linear positioning . This allows automatic mapping from the received signal strength to the position on a line, serving as a building block for fingerprinting in general environments. Slide also features a channel-based scanning method, which acquires fingerprint location after each Wi-Fi channel scanning, to mitigate the fingerprint misalignment problem found in the general mobile fingerprinting. Quantitative analysis and experimental results show that slide is faster than the manual fingerprinting method by up to an order of magnitude with comparable positioning accuracy, and is also more efficient than state-of-the-art mobile fingerprinting methods.

Description: Gesturing is an instinctive way of communicating to present a specific meaning or intent. Therefore, research into sign language interpretation using gestures has been explored progressively during recent decades to serve as an auxiliary tool for deaf and mute people to blend into society without barriers. In this paper, a smart sign language interpretation system using a wearable hand device is proposed to meet this purpose. This wearable system utilizes five flex-sensors, two pressure sensors, and a three-axis inertial motion sensor to distinguish the characters in the American sign language alphabet. The entire system mainly consists of three modules: 1) a wearable device with a sensor module; 2) a processing module; and 3) a display unit mobile application module. Sensor data are collected and analyzed using a built-in embedded support vector machine classifier. Subsequently, the recognized alphabet is further transmitted to a mobile device through Bluetooth low energy wireless communication. An Android-based mobile application was developed with a text-to-speech function that converts the received textinto audible voice output. Experiment results indicate that a true sign language recognition accuracy rate of 65.7% can be achieved on average in the first version without pressure sensors. A second version of the proposed wearable system with the fusion of pressure sensors on the middle finger increased the recognition accuracy rate dramatically to 98.2%. The proposed wearable system outperforms the existing method, for instance, although background lights, and other factors are crucial to a vision-based processing method, they are not for the proposed system.

Description: Automatic fall detection is an active research area since several years. Basically, this is motivated by the impact that falls have, in terms of mortality, morbidity, and social costs, which make them comparable to road traffic injuries. The early detection of a fall can be critical to reduce the mortality rate and to limit the associated health consequences. Technological solutions designed to automatically detect and notify a fall may be classified into wearable and non-wearable. Among the former ones, the use of specific devices to be worn by the subject is a very common assumption, but it fails to address user’s acceptability issues. In fact, the position of the sensor or its visibility may be perceived as a stigma associated with the primary function of fall detection. To address such an issue, this paper presents a methodology for fall detection that relies on a pair of smart shoes, equipped with force sensors and a tri-axial accelerometer, able to detect a fall and notify it to a supervising system. The instrumented footwear enables the analysis of the subject’s motion and foot orientation, recognizing abnormal configurations. The developed algorithm is not computationally intensive, and therefore, can be easily executed on board the wearable device. Laboratory tests provided satisfactory performances in falls detection and correct classification: on 544 falls and 136 activities of daily living, performed by 17 healthy subjects, a 97.1% accuracy has been achieved. Further experiments involving two elderly users demonstrate the effectiveness of the proposed method in a real-life scenario.

Description: In this letter, we propose a strategy to enhance absorption in the black phosphorus absorber based on a nanocavity structure. By introducing a porous silver layer, an enhanced broadband light absorption can be obtained in the spectral range of 520–820 nm. The optical characteristics of the black phosphorus absorptive layer are thoroughly analyzed by absorption spectra, electric intensity distribution, and power flow distribution. Numerical and analytical analysis revealed that the optical absorption of the black phosphorus layer with a porous silver layer can be enhanced by 50% and 396% at the resonant wavelength of 690 nm for p-polarized and s-polarized incidences, respectively, when compared to that without a silver layer. Furthermore, the short-circuit current density ( $J_{{rm{SC}}}$ ) was calculated for the proposed architecture. The peak value of $J_{{rm{SC}}}$ was more than 18 mA/cm 2 . It is demonstrated that this super absorption structure could find important applications on plasmonic-assisted photovoltaic devices or other opto-electronic devices, which will promote the development of ultrathin on-chip energy harvesting and new thin-film active devices.

Description: We proposed an improved phase-based method by using a filtering window on the low-coherence interferogram. Through theoretical derivation and numerical simulation, we prove the correction of our proposed method that the fringe phase can be demodulated nondestructively after applying a symmetrical filtering window nearby the envelope peak, and our method can enhance system SNR. Since fringe overlap phenomenon arising from narrow bandwidth occurs frequently in single-mode sensing system, this method is especially applicable to remote sensing wherein the localization of interference fringe is difficult using traditional phase-based methods. To verify this method, an experiment with a single-mode fiber Fabry-Perot air pressure sensing system was carried out. The experiment results showed that the precision using our method decreased to less than 0.053 $%$ in full 280 kPa pressure scale and the sensing distance extended to 20 km, which were apparently superior to traditional phase-based methods.

Description: One of the most important applications of THz frequencies is biomedical sensing. However, in a THz range, surface plasmon waves on flat metals are not confined and therefore cannot be used for subwavelength sensing. But, it has been shown that graphene can support surface waves at THz frequencies, which has similar properties as plasmonic waves in an optical range. In this paper, a highly sensitive gas sensor in the terahertz frequencies by exciting surface plasmon resonance (SPR) of graphene is proposed. The results show that the proposed SPR gas sensor has high stability and high sensitivity ( S ), and the highest S max (∼147°/RIU) has been obtained by optimizing the Fermi energy, the thickness of the dielectric layer, and the incident light frequency. Moreover, the S of the proposed THz sensor for different refractive index (RI) of gas sensing medium ( n 1 ) is also discussed.

Description: This paper presents a comprehensive investigation of the impedance characteristics of power distribution networks (PDNs) made of carbon nanotube through-silicon vias (CNT-TSVs). The equivalent circuit model of the CNT-TSV array is presented and validated through three-dimensional full-wave electromagnetic simulator up to 100 GHz. By virtue of the circuit model, the inductive properties of CNT-TSVs are characterized and compared for various physical parameters. Then, the PDN impedance characteristics of multiple stacked chip-PDNs with CNT-TSVs are captured and evaluated. It is found that the large CNT kinetic inductance may limit the PDN frequency range. Therefore, the fabrication of CNT-TSVs should be improved to increase the CNT density and reduce the contact resistance.

Description: In this paper, fast capacitor assignment algorithms capable of finding a decoupling solution scheme with a minimum number of components that meets a predefined target impedance with a semi-arbitrary shape within a few seconds to an hour for a given power distribution network (PDN) are proposed. The proposed algorithms also provide identification of shadowed decap ports in a PDN based on an inductance matrix extraction from the given PDN model. Elimination of those shadowed decap ports with the proposed algorithms enables more effective layouts and cost savings on PCB designs.

Description: The aim of this contribution is to develop a procedure able to identify the optimal parameters for the design of a power delivery network of complex high-speed digital systems. A multiple-objective optimization procedure, based on the differential evolutionary algorithm, is proposed and applied to a power delivery network. Results are discussed in terms of performances of the algorithm and in terms of physical parameters of the delivery network. Some limitations are highlighted and the next research steps commented.

Description: In order to realize the ultrawideband suppression of simultaneous switching noise (SSN), a hybrid-embedded novel electromagnetic band-gap (EBG) structure is proposed. The presented EBG structure is based on the traditional Z-bridge EBG embedded the L-bridge EBG structure. By the HFSS software simulation and real test, the results show that the proposed EBG structure can obtain ultrawideband suppression of SSN. Compared with the traditional Z-bridge and L-bridge, the suppression effect is greatly improved. This paper analyzes the reason that the new structure can achieve ultrawideband suppression of SSN based on the equivalent circuit model of the structure. Moreover, the proposed structure will lead to signal integrity problems, which is analyzed by eye diagrams.

Description: This paper studies external fields coupling with two connected transmission lines over different reference planes and develops a new model for this problem. The proposed model is the same with that of the two connected transmission lines over the same reference plane except the connection condition. Two connected transmission lines with different reference planes can be equivalent to two transmission lines over the same reference plane along with an additional voltage at the connection. The results obtained by the proposed model are in a good agreement with those of the full wave method while the approximate method, where the transmission line models of the two lines are connected directly, has large errors. The feature selective validation evaluation results show that the proposed model is “Very good” or “Good.” The proposed model can be applied to analyze fields coupling with connected lines, which are on different walls in a cavity. It is also convenient to be combined with circuit analysis to study electromagnetic pulse effects on circuits on different cavity walls connected by transmission lines.

Description: A novel broadband bandpass frequency-selective surface (FSS) designed for fifth generation (5G) EMI shielding is proposed in this paper. This new design employs the vertical vias into the 2-D periodic arrays, and such a single 2.5-D periodic layer of via-based structure is demonstrated to produce a highly stable angular response up to 60° for both TE and TM polarizations. By cascading two layers of such 2.5-D periodic arrays, the proposed FSS is able to obtain a broad passband as well as the wide out-of-band rejection. Moreover, it has a quite sharp band edge between the passband and the specified stopband. A corresponding equivalent circuit model (ECM) is further developed for better analysis of the operating principle. Finally, a prototype working at the center frequency of around 28 GHz is fabricated and measured. The main novelty of this paper is introducing the 2.5-D concept into designing a wideband FSS, and further reduce the unit size as well as improve the angular stability. Favorable agreement is achieved among the 3-D full-wave simulation, ECM and measurement. All these results demonstrate that the proposed FSS is a good candidate for 5G EMI shielding.

Description: This paper presents experimental results obtained from the Guangdong comprehensive observation experiment on lightning discharge during summer 2014. Residual voltages and current flows in a surge protective device (SPD) connected to an overhead distribution line were observed due to nearby M-components of a triggered lightning flash. Residual voltages with varying characteristics caused by different M-components are analyzed at two terminals of the SPD, and corresponding formation mechanisms for the different characteristics are also discussed. Our results show that the residual voltages at two terminals of the SPD caused by three types of M-component are determined from both the line induction and the ground potential rise (GPR) in a nearby triggered lightning at 40 m distance. The M-component with a large peak current would produce large surge energies in the power line. Under a given peak current, the M-component has greater surge energy than the return stroke. The ground terminal of the SPD is still affected by the GPR, and our results also show that the continuing current superimposed with M-components is an important factor in determining the magnitude of line coupling in power distribution lines when a lightning flash occurs nearby.