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The Chang’e-4 lander successfully landed in the Von Kármán crater on the farside of the Moon in 2019, collecting a large amount of scientific data to analyze the surface material and subsurface structures of the Von Kármán crater. In this study, we processed the high-frequency radar data from the first 25 lunar days collected by the Lunar Penetrating Radar along the route of the Yutu-2 rover. Using the peak frequency shift method, we calculated the loss tangent of the shallow regolith layer ranged from 3×10 −3 to 5.5×10 −3 . The estimated TiO 2 and FeO content in the regolith is 11.2 wt% - 14.7 wt%, revealing a heterogeneous distribution of iron and titanium content along the CE-4 landing site.

Objectives To compare image quality between a deep learning image reconstruction (DLIR) algorithm and conventional iterative reconstruction (IR) algorithms in dual-energy CT (DECT) and to assess the impact of these algorithms on radiomics robustness. Methods A phantom with clinical-relevant densities was imaged on seven DECT scanners with the same voxel size using typical abdominal-pelvis examination protocols. On one DECT scanner, raw data were reconstructed using both conventional IR (adaptive statistical iterative reconstruction-V, ASIR-V) and DLIR. Nine sets of corresponding images were generated on other six DECT scanners using scanner-equipped conventional IR. Regions of interest were delineated through rigid registrations. Image quality was compared. Pyradiomics platform was used for radiomics feature extraction. Test-retest repeatability was assessed by Bland-Altman analysis for repeated scans. Inter-reconstruction algorithm reproducibility between conventional IR and DLIR was tested by intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC). Inter-scanner reproducibility was evaluated by coefficient of variation (CV) and quartile coefficient of dispersion (QCD). Robust features were identified. Results DLIR significantly improved image quality. Ninety-four radiomics features were extracted and nine features were considered as robust. 93.87% features were repeatable between repeated scans. ASIR-V images showed higher reproducibility to other conventional IR than DLIR (ICC mean, 0.603 vs 0.558, p = 0.001; CCC mean, 0.554 vs 0.510, p = 0.004). 7.45% and 26.83% features were reproducible among scanners evaluated by CV and QCD, respectively. Conclusions DLIR improves quality of DECT images but may alter radiomics features compared to conventional IR. Nine robust DECT radiomics features were identified. Key Points • DLIR improves DECT image quality in terms of signal-to-noise ratio and contrast-to-noise ratio compared with ASIR-V and showed the highest noise reduction rate and lowest peak frequency shift. • Most of radiomics features are repeatable between repeated DECT scans, while inter-reconstruction algorithm reproducibility between conventional IR and DLIR, and inter-scanner reproducibility, are low. • Although DLIR may alter radiomics features compared to IR algorithms, nine radiomics features survived repeatability and reproducibility analysis among DECT scanners and reconstruction algorithms, which allows further validation and clinical-relevant analysis.

In actual industrial applications, the defect detection performance of deep learning models mainly depends on the size and quality of training samples. However, defective samples are difficult to obtain, which greatly limits the application of deep learning-based surface defect detection methods to industrial manufacturing processes. Aiming at solving the problem of insufficient defective samples, a surface defect detection method based on Frequency shift-Convolutional Autoencoder (Fs-CAE) network and Statistical Process Control (SPC) thresholding was proposed. The Fs-CAE network was established by adding frequency shift operation on the basis of the CAE network. The loss of high-frequency information can be prevented through the Fs-CAE network, thereby lowering the interference to defect detection during image reconstruction. The incremental SPC thresholding was introduced to detect defects automatically. The proposed method only needs samples without defects for model training and does not require labels, thus reducing manual labeling time. The surface defect detection method was tested on the air rudder image sets from the image acquisition platform and data augmentation methods. The experimental results indicated that the detection performance of the method proposed in this paper was superior to other surface defect detection methods based on image reconstruction and object detection algorithms. The new method exhibits low false positive rate (FP rate, 0%), low false negative rate (FN rate, 10%), high accuracy (95.19%) and short detection time (0.35 s per image), which shows great potential in practical industrial applications.

A novel, high surface encoding capacity compact planar multiresonator tailored for Chipless RFID tag applications is discussed in this article. The tag consists of three hexagonal open loop resonators that are etched on the ground plane of a 50Ω microstrip transmission line. It operates within the frequency range of 2.12 GHz to 5.45 GHz, with a bandwidth of 3.33 GHz. Frequency Shift Coding is employed to record the tag's identification in the spectral domain. A maximum of 343 distinct code words can be generated utilizing three resonators. A notable feature of this tag is its capability to achieve distinct resonating frequencies by adjusting the overall dimensions of the slot. The tag prototype is designed and fabricated on an RT5880 lossy substrate, characterized by loss tangent of 0.0009 and dielectric constant of 2.2. Experimental data from actual prototypes are presented to verify the dependability of the suggested design.

Recent advances in high-field (≥7 T) MRI have made it possible to study the fine structure of the human brain at the level of fiber bundles and cortical layers. In particular, techniques aimed at detecting MRI resonance frequency shifts originating from local variation in magnetic susceptibility and other sources have greatly improved the visualization of these structures. A recent theoretical study [He X, Yablonskiy DA (2009) Proc Natl Acad Sci USA 106:13558–13563] suggests that MRI resonance frequency may report not only on tissue composition, but also on microscopic compartmentalization of susceptibility inclusions and their orientation relative to the magnetic field. The proposed sensitivity to tissue structure may greatly expand the information available with conventional MRI techniques. To investigate this possibility, we studied postmortem tissue samples from human corpus callosum with an experimental design that allowed separation of microstructural effects from confounding macrostructural effects. The results show that MRI resonance frequency does depend on microstructural orientation. Furthermore, the spatial distribution of the resonance frequency shift suggests an origin related to anisotropic susceptibility effects rather than microscopic compartmentalization. This anisotropy, which has been shown to depend on molecular ordering, may provide valuable information about tissue molecular structure.

To establish ubiquitous and energy-efficient wireless sensor networks (WSNs), short-range Internet of Things (IoT) devices require Bluetooth low energy (BLE) technology, which functions at 2.4 GHz. This study presents a novel approach as follows: a fully integrated all-digital phase-locked loop (ADPLL)-based Gaussian frequency shift keying (GFSK) modulator incorporating two-point modulation (TPM). The modulator aims to enhance the efficiency of BLE communication in these networks. The design includes a time-to-digital converter (TDC) with the following three key features to improve linearity and time resolution: fast settling time, low dropout regulators (LDOs) that adapt to process, voltage, and temperature (PVT) variations, and interpolation assisted by an analog-to-digital converter (ADC). It features a digital controlled oscillator (DCO) with two key enhancements as follows: ΔΣ modulator dithering and hierarchical capacitive banks, which expand the frequency tuning range and improve linearity, and an integrated, fast-converging least-mean-square (LMS) algorithm for DCO gain calibration, which ensures compliance with BLE 5.0 stable modulation index (SMI) requirements. Implemented in a 28 nm CMOS process, occupying an active area of 0.33 mm2, the modulator demonstrates a wide frequency tuning range of from 2.21 to 2.58 GHz, in-band phase noise of −102.1 dBc/Hz, and FSK error of 1.42% while consuming 1.6 mW.

Auditory motion perception is one crucial capability to decode and discriminate the spatiotemporal information for neuromorphic auditory systems. Doppler frequency‐shift feature and interaural time difference (ITD) are two fundamental cues of auditory information processing. In this work, the functions of azimuth detection and velocity detection, as the typical auditory motion perception, are demonstrated in a WOx‐based memristive synapse. The WOx memristor presents both the volatile mode (M1) and semi‐nonvolatile mode (M2), which are capable of implementing the high‐pass filtering and processing the spike trains with a relative timing and frequency shift. In particular, the Doppler frequency‐shift information processing for velocity detection is emulated in the WOx memristor based auditory system for the first time, which relies on a scheme of triplet spike‐timing‐dependent‐plasticity in the memristor. These results provide new opportunities for the mimicry of auditory motion perception and enable the auditory sensory system to be applied in future neuromorphic sensing. A auditory sensory system with motion perception is demonstrated by using a WOx‐based memristive synapse. Due to the coexistence of the volatile mode and semi‐nonvolatile mode in the Ar‐plasma‐treated (APT) WOx memristor, the functions of azimuth detection and velocity detection are realized via implementing the high‐pass filtering and processing the spike trains with frequency shift in both modes, respectively.

The Chinese Chang’E-5 probe landed in the Mons Rümker of Oceanus Procellarum on the near side of the Moon. The lunar regolith penetrating radar (LRPR) carried by the Chang’E-5 probe allows for the determination of in situ lunar regolith dielectric properties, which are probably related to the age and chemical composition of the regolith. In this paper, we analyze the Chang’E-5 LRPR data with the frequency shift method to estimate the loss tangent of the lunar regolith within a depth of ∼2.8 m. The loss tangent of the Chang’E-5 landing site is constrained to be 0.0148 ± 0.0016, which is substantially higher than that of the typical lunar regolith. The high loss tangent is found to be characteristic of the young basalt age (∼2.0 Ga) and high TiO2+FeO content (28.21 ± 1.57%) of the Chang’E-5 landing site. Integrated analysis of results from Chang’E-3, Chang’E-4, and Chang’E-5 show that the younger is the geologic age of the mare unit, the greater is the loss tangent of the lunar regolith, and the weaker is the radar electromagnetic signal penetrating ability.

In this study, we experimentally showcase the microfiber evanescent-field photothermal gas detection by exploiting all-fiber MHz-level frequency shift scheme. Based on the acousto-optic interaction effect, the low-frequency shifts of 0.9 MHz and 1.83 MHz can be obtained through the cyclic conversion between the transverse core modes LP and LP in the few-mode fiber. Our proposed all-fiber frequency shifters show flexible MHz-level up(down) frequency shifts with superior sideband rejection ratio (over 40 dB) and low insertion loss (less than 1 dB). Furthermore, an all-fiber heterodyne interferometric detection system is implemented by leveraging the above low-frequency shifters, in which around 1-μm-diameter microfiber is investigated for photothermal gas detection. A pump-probe configuration is employed to obtain the photothermal effect induced by the gas absorption of the modulated evanescent field. By demodulating the phase of the beat signal output by the interferometer, an equivalent detection limit (1 ) of 32 ppm and a response time of 22 s are achieved for ammonia, as well as 0.24 % instability within 48 pump cycles. Given its compact all-fiber configuration and high sensitivity with fast response, the experimental results can pave the way for widespread applications like heterodyne detection, fiber optical sensors, and interplanetary coherent communications.

The higher efficiency of superconducting radio-frequency (SRF) cavities compared to normal-conducting ones enables the development of high-energy continuous-wave linear accelerators (linacs). Recent progress in the development of high-qualityNb3Snfilm coatings along with the availability of cryocoolers with high cooling capacity at 4 K makes it feasible to operate SRF cavities cooled by thermal conduction at relevant accelerating gradients for use in accelerators. A possible use of conduction-cooled SRF linacs is for environmental applications, requiring electron beams with energy of 1–10 MeV and 1 MW of power. We have designed a 915 MHz SRF linac for such an application and developed a prototype single-cell cavity to prove the proposed design by operating it with cryocoolers at the accelerating gradient required for 1 MeV energy gain. The cavity has a∼3μmthickNb3Snfilm on the inner surface, deposited on a∼4mmthick bulk Nb substrate and a bulk∼7mmthick Cu outer shell with three Cu attachment tabs. The cavity was tested up to a peak surface magnetic field of 53 mT in liquid He at 4.3 K. A horizontal test cryostat was designed and built to test the cavity cooled with three Gifford-McMahon cryocoolers. The rf tests of the conduction-cooled cavity, performed at General Atomics, achieved a peak surface magnetic field of 50 mT and stable operation was possible with up to 18.5 W of rf heat load. The peak frequency shift due to microphonics was 23 Hz. These results represent the highest peak surface magnetic field achieved in a conduction-cooled SRF cavity to date and meet the requirements for a 1 MeV energy gain.