Resolution Performance Research Articles

Assessment of Galileo FOC + IOV Signals and Geometry-Based Single-Epoch Resolution of Quad-Frequency Carrier Ambiguities

Galileo can independently provide navigation and positioning services globally. Galileo satellites transmit quad-frequency E1, E5a, E5b, and E5 signals, which can benefit the integer ambiguity rapid resolution. Firstly, the qualities of Galileo signals from Carrier-to-Noise (C/N0), Multipath Combination (MPC), and pseudo-range and phase noise using the ultra-short baseline were evaluated. The experimental results indicated that the Galileo E5 signal has the highest C/N0, while the C/N0 of other signals is lower and almost equal. In terms of MPC, the Galileo E1 was the most severe followed by E5a and E5b, and the MPC of E5 is less severe. As for the precision of un-differenced observations, the carrier phase and pseudo-range observations of Galileo E5 had higher accuracy than those of Galileo E5a, E5b, and E1. Secondly, the quad-frequency observations allowed for various linear combinations of different frequencies, which provides some feasibility for improving the performance of ambiguity resolution. Assuming that the phase noise σ∇ΔΦ = 0.01 m and the first-order ionosphere σ∇ΔI1 = 1 m, the total noise of the Extra-Wide-Lane (EWL) combination observation ((0, 0, 1, −1) and (0, −1, 1, 0)) and Very-Wide-Lane (VWL) combination observation ((0, −2, 1, 1), (0, −3, 2, 1)) are still less than 0.5 cycles. Finally, a geometry-based quad-frequency carrier ambiguities (GB-QCAR) method was developed, and all different options of linear combinations were investigated systematically from the ambiguity-fixed rate with two baselines. Experimental results demonstrated that, the ambiguity fixed rate of combination observation (0, −1, 1, 0), (0, −3, 5, −2), (1, −1, 0, 0) and (0, 0, 0, 1) is the highest and the positioning accuracy of VWL combination observation (0, −3, 5, −2) is equivalent to that of the EWL combination observation (0, −1, 1, 0). The positioning accuracies of WL combination observation (1, −1, 0, 0) are preferable to 3 cm and 10 cm in the horizontal and vertical, respectively. The positioning accuracy of NL combination observation E5 in the horizontal direction is about 1 cm, and is better than 4 cm in the vertical direction. Therefore, we can use Galileo observations to realize high-precise navigation services utilizing the proposed GB-QCAR method.

A high-resolution panchromatic-multispectral satellite image fusion method assisted with building segmentation

The main difficulty of panchromatic-multispectral image fusion is to balance the quality of spatial information and the spectral fidelity. Most of the practical fusion methods determine the optimal parameters based on the spatial and spectral characteristics of all original panchromatic and multispectral bands. However, for built-up and non-built-up areas (like cropland, forest) in one image, there may be large differences in their spatial and spectral characteristics, so their fused results are not optimal respectively with same parameters. To address above issues, this paper presents a high-resolution satellite image fusion method assisted with building segmentation. First, the proposed approach computes the average gradient and Gaussian filtering parameters of built-up and non-built-up areas separately according to the building segmentation results, on the basis of smoothing filter-based intensity modulation (SFIM). Then the intermediate data of two types of areas are computed in parallel and they are composited to obtain the final fused image, weighted by the pixel-wise “building factors” derived from the building segmentation results. Moreover, to better simulate the spatial characteristics of the multispectral image, we perform the “gradient simulation” operation to extract the gradient values in the multispectral image. Experimental results on Jilin-1 satellite images show that the proposed method provides competitive performance in spatial resolution, multispectral fidelity and quantity of information, as compared to the state-of-the-art methods in mainstream commercial software.

The processing network of high-frequency acoustoelectric signal in the living rat brain

Objective. Acoustoelectric brain imaging (ABI) is a potential noninvasive electrophysiological neuroimaging method with high spatiotemporal resolution. At the focal spot of the focused ultrasound, with the couple of acoustic and electric fields, high-frequency acoustoelectric (HF AE) signal is generated. Because the brain is a volume conductor, HF AE signal can be detected in other brain cortex. The processing of HF AE signal is critical for improving decoding precision, further improving the spatial resolution performance of ABI. This study investigates the processing network of HF AE signal in the living rat brain. Approach. When HF AE generated on the left primary visual cortex (V1-L), low-frequency (LF) electroencephalography and HF AE signals on different cortex were recorded at the same time. Firstly, AE signal on different sides of the brain cortex were compared, including prefrontal cortex (FrA) and primary somatosensory cortex (S1FL). Then, we constructed and analyzed functional networks of two signals. Main results. In the same cortex, HF AE signal on the right side had stronger intensity. And compared with LF networks, HF AE network had larger global efficiency and shorter characteristic path length, denoting the stronger processing and transmission of AE signal. Additionally, in HF AE network, the node had significantly increased local properties and the connection were concentrated in the occipital lobe, reflecting the occipital lobe plays an important role in the processing. Significance. Experiment results demonstrate that, compared with LF network, HF AE network is more efficient and had stronger transmission capabilities. And the connection of HF AE network is concentrated in the occipital lobe. This work preliminarily reveals the HF AE signal processing, which is significant for improving the ABI quality and provides a new insight for understanding the brain HF signal.

Development of a compact and cost-effective PET detector module for a small-animal PET system with FESA ASIC

Due to the high cost and large channel number in positron emission tomography (PET) systems, the integration level and cost performance must be considered in the construction of commercial PET systems. In this paper, a highly integrated readout electronic system was designed and implemented based on a self-developed FESA (Front End for SiPM Arrays) readout ASIC; a compact cost-effective detector module with four lined up detector heads was built, and its performance was evaluated. Each detector head consisted of a 24× 24 LYSO crystal array (each crystal element had dimensions of 0.99 × 0.99 × 15 mm3), one end coupling to an 8 × 8 silicon photomultiplier array (SiPM array with dimensions of 3.2 × 3.2 mm2 each), and the other end covered with a 1 mm thick light guide layer. Since the front-end FESA readout chip employed a row-column summing circuit to reduce the readout channels from 64 to 16, we tried a new depth encoding method based on a single-end readout with the structure. The test results showed that the average coincidence time resolution (CTR), energy resolution, and depth of interaction (DOI) resolution of the detector are 413 ps, 15.7%, and 5.2 mm, respectively, while the crystal array in the detector head with 9-to-1 coupling can be clearly separated in the flood image. Compared with the detector head without the depth encoding ability, the clearness of the flood image was slightly decreased, but the energy resolution and time performance remained the same. We also implemented a central control board that connected all detector modules via fiber connections. The data from the detector modules could be collected over the connections, and the system central clock could be precisely distributed; therefore, the compactness of the electronics system was further enhanced.

Black Joy/White Fragility by Joy Mariama Smith

Reviewed by: Black Joy/White Fragility by Joy Mariama Smith Megan Hoetger BLACK JOY/WHITE FRAGILITY. By Joy Mariama Smith. Kunstinstituut Melly, Rotterdam, The Netherlands. October 21, 2021. Occupying a small but central gallery on the main exhibition floor of Rotterdam’s Kunstinstituut Melly, Joy Mariama Smith’s provocatively titled Black Joy/White Fragility brought a queer urban nightlife edge to the institution’s fall 2021 program. As a movement artist, educator, and activist, Smith has spent the last decades cultivating a practice rooted in radical Black traditions of refusal and care, which sits at the intersections of art, pedagogy, performance, design, and club culture. In Black Joy/White Fragility, these elements come together as a performance installation that unsettles the general stasis of the arts institution. In the installation, the props and lighting of a club environment merged with the pedestals and spatial arrangements of an art gallery: crystals and natural oils took their places atop stands as a mixing board, speakers, and subwoofer stood below the gallery’s monumental arched window. In the back corner, a simple neon sign shone in fuchsia pink with the words: “Black Joy.” The soft curves of the cursive lettering and the glittering refraction of the disco ball suspended in the center of the room stood in contrast to the hard shadows of the window’s wrought iron details, counteracting the sharp points of the metalwork with an ephemeral sparkle and a nominal reminder of Black joy. Together with a few strategically placed color LED stage lights, these light-and-shadow plays created a flickering cinematic effect that pulsed with the creeping (sub-)bass of Smith’s techno music playlist (featuring Seven Angels, KILLA, Sophie Ruston, and DJ NEON QUEEN). Literally shaking the bean bags in painter Iris Kensmil’s adjacent gallery of portraiture with deep sonic pulsations, Smith’s installation was something that could be felt before it was legible as something “to be heard.” Starting from a place of resonances, then, Black Joy/White Fragility worked through vibrations, which cut across visual, architectural, and other boundaries. The artist described this in conversation with me as “trying to heal, trying to vibrate the building.” The link between healing and vibrating says much about the dramaturgy of the performance that activated Smith’s installation. On four days throughout the month-long run of their project, the installation was closed to museumgoers and reserved for a community of QTBIPOC (Queer, Trans, Black, Indigenous, People of Color) performers, including Sharlan Adams, Esther Arribas, Ieva Barsauskaite, Carly Rose Bedford, Mohamed Boujarra, Devika Chotoe, Dandelion Eghosa, Antonella Fittipaldi, G, Ahmed El Gendy, Ciro Goudsmit, Annick Kleizen, Isabel Kwarteng, Parisa Madani, Mini Maxwell, Anthony Nestel, Emanuel Oladokun, Auro Orso, Ada M. Patterson, Roberto Perez Gayo, Estrellx Supernova, June Yuen Ting, and Michael Ludwig Tsouloukidse. The performers could dance, rest, or converse with one another as they pleased. In this occupation otherwise, the installation took on a double presence: it was an architecturally scaled social sculpture and a site of convening. Working in and against the spatial cues of white (cube) space, it moved beyond contained abstract notions of language and action, and into the infrastructures of the building where it inverted patterns of racial segregation, confusing both the directionality of the gaze (who was seeing whom?) and exclusionary door policies (visitors and allied white performers could only encounter “the club” from outside the doors of the gallery). And within this expanded social sculpture, a site of convening was carved out, holding space open for the community of performers to gather and share time. What “gathering” meant remained an open invitation: performers could dance together in the installation or dance autonomously with wireless headphones. They could also leave the gallery and move through the art center’s circulation spaces (entryway, bookshop, [End Page 368] halls, stairways, and elevator) with their wireless headphones. Donning oversized and often hand-altered neon T-shirts designed by Smith with inscriptions like “Hard Femme,” “Stop Acting White,” or “Queer Energetic Household,” they were immediately recognizable as a community of performers, but without an expected precondition of always acting together. Click for larger view View full resolution Performance documentation of Joy Mariama Smith, Black Joy...

Data-driven head motion correction for PET using time-of-flight and positron emission particle tracking techniques.

Positron emission tomography (PET) is susceptible to patient movement during a scan. Head motion is a continuing problem for brain PET imaging and diagnostic assessments. Physical head restraints and external motion tracking systems are most commonly used to address to this issue. Data-driven methods offer substantial advantages, such as retroactive processing but typically require manual interaction for robustness. In this work, we introduce a time-of-flight (TOF) weighted positron emission particle tracking (PEPT) algorithm that facilitates fully automated, data-driven head motion detection and subsequent automated correction of the raw listmode data. We used our previously published TOF-PEPT algorithm Dustin Osborne et al. (2017), Tasmia Rahman Tumpa et al., Tasmia Rahman Tumpa et al. (2021) to automatically identify frames where the patient was near-motionless. The first such static frame was used as a reference to which subsequent static frames were registered. The underlying rigid transformations were estimated using weak radioactive point sources placed on radiolucent glasses worn by the patient. Correction of raw event data were achieved by tracking the point sources in the listmode data which was then repositioned to allow reconstruction of a single image. To create a "gold standard" for comparison purposes, frame-by-frame image registration based correction was implemented. The original listmode data was used to reconstruct an image for each static frame detected by our algorithm and then applying manual landmark registration and external software to merge these into a single image. We report on five patient studies. The TOF-PEPT algorithm was configured to detect motion using a 500 ms window. Our event-based correction produced images that were visually free of motion artifacts. Comparison of our algorithm to a frame-based image registration approach produced results that were nearly indistinguishable. Quantitatively, Jaccard similarity indices were found to be in the range of 85-98% for the former and 84-98% for the latter when comparing the static frame images with the reference frame counterparts. We have presented a fully automated data-driven method for motion detection and correction of raw listmode data. Easy to implement, the approach achieved high temporal resolution and reliable performance for head motion correction. Our methodology provides a mechanism by which patient motion incurred during imaging can be assessed and corrected post hoc.

Centimeter-level positioning by instantaneous lidar-aided GNSS ambiguity resolution

High-precision vehicle positioning is key to the implementation of modern driving systems in urban environments. Global Navigation Satellite System (GNSS) carrier phase measurements can provide millimeter- to centimeter-level positioning, provided that the integer ambiguities are correctly resolved. Abundant code measurements are often used to facilitate integer ambiguity resolution (IAR); however, they suffer from signal blockage and multipath effects in urban canyons. In this contribution, a light detection and ranging (lidar)-aided instantaneous ambiguity resolution method is proposed. Lidar measurements, in the form of 3D keypoints, are generated by a learning-based point cloud registration method using a pre-built high-definition map and integrated with GNSS observations in a mixed measurement model to produce precise float solutions, which in turn increase the ambiguity success rate. Closed-form expressions of the ambiguity variance matrix and the associated Ambiguity Dilution of Precision (ADOP) are developed to provide a priori evaluation of such lidar-aided ambiguity resolution performance. Both analytical and experimental results show that the proposed method enables successful instantaneous IAR with limited GNSS satellites and frequencies, leading to centimeter-level vehicle positioning.

A real-time combined quality control method for GNSS precise positioning in harsh environments

Global Navigation Satellite System (GNSS) precise positioning can be significantly affected by severe multipath effects and outliers in harsh environments, and highly relies on quality control strategies. Previous studies mainly focus on the posterior residuals to check and exclude the outliers in GNSS observations, limited work emphasizes the combined quality control method considering both the prior and posterior knowledge simultaneously. This paper proposed a real-time combined quality control method to process the multipath effects and outliers in harsh environments simultaneously. Specifically, in the prior stage, a modified multipath processing strategy is proposed for both phase and code observations, then a modified detection, identification, and adaptation (DIA) method considering the maximum times of data snooping is studied in the posterior stage. Two dedicated experiments in real harsh environments were carried out to evaluate the performance of the proposed combined quality control method. For the static experiment, the proposed method exhibits smaller positioning errors, the best positioning accuracy, and the highest availability in this study. Specifically, the proposed method exhibits an improved percentage of 55.4 %, 56.3 %, and 59.7 % for positioning accuracy compared to those without the quality control method in the E, N, and U directions, respectively. Besides, the proposed method can further improve the performance of ambiguity resolution with an improved percentage of 32.2 %. For the kinematic experiment, the three-dimensional positioning accuracy of the proposed method is 0.577 m, which exhibits a 40.0 % improvement compared to those without the quality control method. Also, the proposed method exhibits better performance under relatively strong multipath effects. In this sense, the proposed real-time combined quality control method is highly appreciated in terms of positioning availability, accuracy, and ambiguity resolution for GNSS precise positioning, especially in harsh environments.

Adaptive beamforming based on minimum variance (ABF-MV) using deep neural network for ultrafast ultrasound imaging

Ultrafast ultrasound imaging can achieve high frame rate by emitting planewave (PW). However, the image quality is drastically degraded in comparison with traditional scanline focused imaging. Using adaptive beamforming techniques can improve image quality at cost of real-time performance. In this work, an adaptive beamforming based on minimum variance (ABF-MV) with deep neural network (DNN) is proposed to improve the image performance and to speed up the beamforming process of ultrafast ultrasound imaging. In particular, a DNN, with a combination architecture of fully-connected network (FCN) and convolutional autoencoder (CAE), is trained with channel radio-frequency (RF) data as input while minimum variance (MV) beamformed data as ground truth. Conventional delay-and-sum (DAS) beamformer and MV beamformer are utilized for comparison to evaluate the performance of the proposed method with simulations, phantom experiments, and in-vivo experiments. The results show that the proposed method can achieve superior resolution and contrast performance, compared with DAS. Moreover, it is remarkable that both in theoretical analysis and implementation, our proposed method has comparable image quality, lower computational complexity, and faster frame rate, compared with MV. In conclusion, the proposed method has the potential to be deployed in ultrafast ultrasound imaging systems in terms of imaging performance and processing time.

The coordinate sensitive detector with high space and time resolution based on the MA-20 multianode PMT

The work is dedicated to the discussion of the possibility of creating a position-sensitive detector with high coordinate reconstruction. The paper presents the simulation results and the experimentally obtained data for a prototype detector based on the MA-20 multianode PMT [1] and a linear stack of scintillating crystal or plastic strips. The multianode position-sensitive PMT MA-20 has a semitransparent bi-alkaline photocathode with the size of the sensitive area of 10 × 200 mm2, 10 evaporated type bi-alkaline type dynodes of the same length, and 20 separated anodes. This PM is the invention of the authors. The maximum gain of the dynode system is 106. The stack of scintillating strips made of GSO (gadolinium orthosilicate) crystals with an element size of 3 × 10 × 50 mm3, of BGO (bismuth germanate) crystals with an element size of 5 × 15 × 40 mm3, and finally stack of strips made of a plastic scintillator with an element size of 5 × 10 × 200 mm3 were used for experimental measurement of a spatial resolution of the detector prototype. Space resolution was determined by the position of the center of gravity of charges of neighboring anodes [2]. As a source of radiation, the collimated 137Cs (γ 0.662 MeV) and 90Sr (β− 2.283 MeV) were used, the measured number of photoelectrons is 10–20 of one element of the stack, depending on the scintillating strip type. The use of a multi-anode photomultiplier in combination with the stack of crystal or plastic scintillators allows one to get a simple linear detector with high performance in spatial resolution and also with a low level of intrinsic noise in comparison, for example, with silicon PMT. A resolution simulation was performed for a system consisting of a one-dimensional stack of scintillation strips placed on the photocathode of a multi-anode PMT for different values of the strips width and the number of photoelectrons of one strip. The experimental dependences of the signal value versus position of optical fiber with a diameter of 1 mm on the photocathode of the 20 anodes PMT were also measured that allowed to specify the coordinate resolution for the described detector. As a result of processing the collected data, spatial resolution was obtained at the level of 1 mm. The obtained results are in good agreement with the simulation results.

LiCo: Toward Lightweight Resolution of Signal Collisions in LoRaWAN

This letter proposes a novel technique named LiCo to resolve LoRa signal collisions. Unlike existing approaches that introduce considerable computational overhead due to redundant LoRa demodulation operations, LiCo aims at a more lightweight way by simply performing one-shot demodulation regarding all colliding signals. For the separation of colliding signals, LiCo further analyzes the demodulation results in a comparative manner with no need to apply any complicated arithmetic. Theoretical and experimental results show that LiCo can reduce the computational overhead while achieving similar collision resolution performance as the state of the art.

Preparation and evaluation of a chiral porous organic cage based chiral stationary phase for enantioseparation in high performance liquid chromatography

Porous organic cages (POCs) are a new kind of porous molecular materials, which have gained widespread interest in many fields due to their intriguing properties, including excellent molecular solubility, inherent molecular cavity and rich host-guest chemistry. To date, many chiral POCs have been explored as chiral stationary phases (CSPs) for gas chromatographic (GC) separation of enantiomers. However, the applications of chiral POCs for high performance liquid chromatography (HPLC) enantiomeric separation is extremely rare. In this study, we report the construction of thiol-ene click reaction for the preparation of CSP for HPLC by using a [4+8]-type chiral POC NC4-R as chiral selector. The fabricated CSP showed good chiral resolution performance not only in normal-phase HPLC (NP-HPLC) but also in reversed-phase HPLC (RP-HPLC). Seventeen and ten racemates were well resolved in the two separation modes, respectively, including ketones, esters, alcohols, phenols, amines, ethers, organic acids, and amino acids. Moreover, the fabricated column also shows good chiral recognition complementarity to two popular chiral HPLC columns (Chiralpak AD-H and Chiralcel OD-H columns) and previously reported chiral POC NC1-R-based HPLC column, which can resolve some racemates that unable to be resolved by the two commercially available chiral HPLC columns and NC1-R-based column. The relative standard deviation (RSD) values (n = 4) of retention time and resolution (Rs) of analytes separated on the column were less than 0.3 % and 0.5 % after it was subjected to different injections, showing the good reproducibility and stability of the NC4-R-based column. This work demonstrated high potentials of chiral POCs for HPLC enantioseparation and the applicability of chiral POC-based HPLC columns can be broadened by developing more chiral POCs with diverse structures as chiral selector for HPLC.

Multi-GNSS-Weighted Interpolated Tropospheric Delay to Improve Long-Baseline RTK Positioning.

Until now, RTK (real-time kinematic) and NRTK (Network-based RTK) have been the most popular cm-level accurate positioning approaches based on Global Navigation Satellite System (GNSS) signals in real-time. The tropospheric delay is a major source of RTK errors, especially for medium and long baselines. This source of error is difficult to quantify due to its reliance on highly variable atmospheric humidity. In this paper, we use the NRTK approach to estimate double-differenced zenith tropospheric delays alongside ambiguities and positions based on a complete set of multi-GNSS data in a sample 6-station network in Europe. The ZTD files published by IGS were used to validate the estimated ZTDs. The results confirmed a good agreement, with an average Root Mean Squares Error (RMSE) of about 12 mm. Although multiplying the unknowns makes the mathematical model less reliable in correctly fixing integer ambiguities, adding a priori interpolated ZTD as quasi-observations can improve positioning accuracy and Integer Ambiguity Resolution (IAR) performance. In this work, weighted least-squares (WLS) were performed using the interpolation of ZTD values of near reference stations of the IGS network. When using a well-known Kriging interpolation, the weights depend on the semivariogram, and a higher network density is required to obtain the correct covariance function. Hence, we used a simple interpolation strategy, which minimized the impact of altitude variability within the network. Compared to standard RTK where ZTD is assumed to be unknown, this technique improves the positioning accuracy by about 50%. It also increased the success rate for IAR by nearly 1.

Progress in Color Conversion Technology for Micro‐LED

AbstractWith the continuous improvement of display demand in scientific research and the market, Micro‐light‐emitting diode (LED) has emerged as a new generation of display technology. With its excellent performance in color, resolution, life, and energy consumption, Micro‐LED has shined brilliantly in the display market in recent years. This review introduces the methods for realizing Micro‐LED full‐color display through color conversion methods from the perspective of existing technologies, including the preparation of the Micro‐LED chip, the research process from the early passive matrix driving method to the active matrix driving method, and the preparation method of the color conversion layer by inkjet printing, photolithography, and nanoimprinting. The current research achievements and challenges encountered in Micro‐LED are systematically described. It is intended to provide readers and researchers with some inductive research materials and improvement ideas, and further promote the development of Micro‐LED.

The sparse readout RIGEL Application Specific Integrated Circuit for Pixel Silicon Drift Detectors in soft X-ray imaging space applications

An Application Specific Integrated Circuit (ASIC), called RIGEL, designed for the sparse readout of a Silicon Pixel Drift Detector (PixDD) for space applications is presented. The low leakage current (less than 1 pA at +20 °C) and anode capacitance (less than 40 fF) of each pixel (300 μm × 300 μm) of the detector, combined with a low-noise electronics readout, allow to reach a high spectroscopic resolution performance even at room temperature. The RIGEL ASIC front-end architecture is composed by a 2-D matrix of 128 readout pixel cells (RPCs), arranged to host, in a 300 μm-sided square area, a central octagonal pad (for the PixDD anode bump-bonding), and the full-analog processing chain, providing a full-shaped and stretched signal. In the chip periphery, the back-end electronics features 16 integrated 10-bits Wilkinson ADCs, the configuration register and a trigger management circuit. The characterization of a single RPC has been carried out whose features are: eight selectable peaking times from 0.5 μs to 5 μs, an input charge range equivalent to 30 keV, and a power consumption of less than 550 μW per channel. The RPC has been tested also with a 4×4 prototype PixDD and 167 eV Full Width at Half Maximum (FWHM) at the 5.9 keV line of 55Fe at 0 °C and 1.8 μs of peaking time has been measured.

Inverse Synthetic Aperture Radar Imaging Using an Attention Generative Adversarial Network

The traditional inverse synthetic aperture radar (ISAR) imaging uses matched filtering and pulse accumulation methods. When improving the resolution and real-time performance, there are some problems, such as the high sampling rate and large amount of data. Although the compressed sensing (CS) method can realize high-resolution imaging with small sampling data, the sparse reconstruction algorithm has high computational complexity and is time-consuming. The imaging result is limited by the model and sparsity hypothesis. We propose a novel CS-ISAR imaging method using an attention generative adversarial network (AGAN). The generator of AGAN is a modified U-net consisting of both spatial and channel-wise attention. The trained generator can learn the imaging operation from down-sampling data to high-resolution ISAR images. Simulations and measured data experiments are given to validate the advantage of the proposed method.

Designing a Winner–Loser Gap for WTA in Subthreshold. Resolution Performance Revisited

The paper pioneers a thorough mathematical approach for the Lazzaro variant of the W(inner) T(ake) A(ll) maximum rank and amplitude analog selector. Two exact levels of output which split the maximum and determine the resolution, are found for the first time. At the input, a list of currents left( I_{1},I_{2},ldots ,I_{N}right) from a large family {{mathcal {L}}} with smallest relative distance Delta on a left[ 0,I_{M}right] scale is applied. To distinguish the largest current I_{w} (the winner) from the second largest I_{l} (the loser), the paper proposes two decision levels, {overline{D}} and {underline{D}}, for the output voltage list left( U_{1},U_{2},ldots ,U_{N}right) . The upper level {overline{D}} is surpassed only by the U_{w} winner and encodes the winning rank w. All other ranks are placed under the lower level {underline{D}}. Two rigorously treated optimization problems with inequality constraints lead to the identification of two input lists that yield the levels {overline{D}} and {underline{D}} as outputs. They are valid for processing any list in the {mathcal {L}} family. The index left( {overline{D}}-{underline{D}}right) /U_{M}—“the output resolution”—expresses how large the gap between the first and the second component on the left[ 0,U_{M}right] scale is. It exceeds “the input resolution,” i.e., the similar index Delta /I_{M} at the input and the two depend monotonically on each other. Widely commented numerical examples are presented.

High efficiency echelle gratings for the far ultraviolet.

Modern grating manufacturing techniques suffer from inherent issues that limit their peak efficiencies. The anisotropic etching of silicon facilitates the creation of custom gratings that have sharp and atomically smooth facets, directly addressing these issues. We describe work to fabricate and characterize etched silicon echelles optimized for the far ultraviolet (FUV; 90-180 nm) bandpass. We fabricate two echelles that have parameters similar to the mechanically ruled grating flown on the Colorado High-resolution Echelle Stellar Spectrograph sounding rocket. We demonstrate a 42% increase in peak order efficiency and an 83% decrease in interorder scatter using these gratings. We also present analysis on where the remaining efficiency resides. These demonstrated FUV echelle improvements benefit the faint source sensitivity and high resolution performance of future UV observatories.

Design and fabrication of an ultra-sensitive Ta2C MXene/Au-coated tilted grating sensor

Accurate evaluation of trace biochemical molecular signals by fiber-optic sensors is highly challenging. Recently, MXene, as one of the most promising 2D materials with unique optoelectronic properties and structural advantages, has attracted numerous concerns about the sensitization of optical fiber sensors. This paper proposed an innovative Ta2C MXene (Ta2C-M) sensitized Au-coated tilted fiber Bragg grating (TFBG) SPR sensor. We achieved the optimal deposition scheme for Ta2C-M by varying the laser induction time. The introduction of Ta2C-M brought a 23.3% increase in sensitivity and exhibited an excellent figure of merit (FOM=2586.11 RIU-1) and linearity (R2 =0.99903). Based on COMSOL, a 3D diversity analysis model was proposed, which validated the polarization response of the TFBG sensor, the electromagnetic gain of the Ta2C-M coating and enabled the fitting evaluation of the SPR behavior. The sensitization mechanism of the Ta2C-M coating was further analyzed utilizing energy band theory based on the Vienna ab initio Simulation Package (VASP). The assessment of two carcinogenic food additives, Saccharin and BHT, demonstrated the extreme SPR signal resolution and accurate trace detection performance (10-11 M) of the Ta2C-M/Au/TFBG sensor. These findings indicate that the proposed sensor will hopefully open new biotechnology, medicine, and food safety detection avenues.

A Novel Method for Diagnosis of Broken Bars Based on Optimum Resolution of Prescient Direction Algorithm

Fourier transformation (FT) and Multiple Signal Classification (MUSIC) method suffer the insufficient ability in diagnosing broken rotor bar (BRB) fault using short-time data. Theoretical and simulation analyses show that the Optimum Resolution of Prescient Direction (ORPD) algorithm has the best frequency resolution performance due to a priori knowledge. The main objective of this paper is to detect BRB faults in induction machines using a condition monitoring architecture based on ORPD algorithm. In the proposed application, the ORPD algorithm with the best frequency resolution performance is used to estimate the fault-sensitive frequencies in the stator current signature. The prior information of BRB fault characteristic distribution is used to construct a weighting matrix in the ORPD algorithm, for acquiring the lowest signal-to-noise ratio resolution threshold. Once frequencies are estimated, their corresponding amplitudes are obtained by using the least squares estimator. The proposed methods were tested using experimental induction motors with different fault severity under the effect of several load levels or supply frequencies. Two types of power supply modes are considered: main and inverter. The results show that compared with traditional method which uses FT and MUSIC algorithm for fault diagnosing, the method based on ORPD algorithm has a higher frequency resolution and identification ability with short-time data, and still has good diagnostic performance even under light loading and lower supply frequencies.