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Background: Increasing attention to liver-bone crosstalk has spurred interest in targeted interventions for various forms of osteoporosis. Liver injury induced by different liver diseases can cause an imbalance in bone metabolism, indicating a novel regulatory paradigm between the liver and bone. However, the role of the liver-bone axis in both primary and secondary osteoporosis remains inadequately elucidated. Therefore, exploring the exact regulatory mechanisms of the liver-bone axis may offer innovative clinical approaches for treating diseases associated with the liver and bone. Methods: Here, we summarize the latest research on the liver-bone axis by searching the PubMed and Web of Science databases and discuss the possible mechanism of the liver-bone axis in different types of osteoporosis. The literature directly reporting the regulatory role of the liver-bone axis in different types of osteoporosis from the PubMed and Web of Science databases has been included in the discussion of this review (including but not limited to the definition of the liver-bone axis, clinical studies, and basic research). In addition, articles discussing changes in bone metabolism caused by different etiologies of liver injury have also been included in the discussion of this review (including but not limited to clinical studies and basic research). Results: Several endocrine factors (IGF-1, FGF21, hepcidin, vitamin D, osteocalcin, OPN, LCAT, Fetuin-A, PGs, BMP2/9, IL-1/6/17, and TNF-α) and key genes (SIRT2, ABCB4, ALDH2, TFR2, SPTBN1, ZNF687 and SREBP2) might be involved in the regulation of the liver-bone axis. In addition to the classic metabolic pathways involved in inflammation and oxidative stress, iron metabolism, cholesterol metabolism, lipid metabolism and immunometabolism mediated by the liver-bone axis require more research to elucidate the regulatory mechanisms involved in osteoporosis. Conclusion: During primary and secondary osteoporosis, the liver-bone axis is responsible for liver and bone homeostasis via several hepatokines and osteokines as well as biochemical signaling. Combining multiomics technology and data mining technology could further advance our understanding of the liver-bone axis, providing new clinical strategies for managing liver and bone-related diseases.The translational potential of this article is as follows: Abnormal metabolism in the liver could seriously affect the metabolic imbalance of bone. This review summarizes the indispensable role of several endocrine factors and biochemical signaling pathways involved in the liver-bone axis and emphasizes the important role of liver metabolic homeostasis in the pathogenesis of osteoporosis, which provides novel potential directions for the prevention, diagnosis, and treatment of liver and bone-related diseases.

ObjectiveThe aim of this study was to investigate whether a potential moral cognitive impairment (failure in understanding moral rules) exists in patients with schizophrenia (SCZ) and to explore the effect of childhood trauma (CT) on moral cognition in a group of patients with SCZ.MethodsA total of 99 patients with SCZ and 102 healthy controls (HCs) were included in this study. The Childhood Trauma Questionnaire-Short Form (CTQ) was administered to assess childhood trauma experiences in both groups, while the Moral Identity Measure (MIM) and the Moral Foundations Questionnaire (MFQ) were applied for a comparative evaluation of moral cognition across the two groups. The Positive and Negative Syndrome Scale (PANSS) was administered to assess the psychopathology.ResultsPatients with schizophrenia had significantly greater CTQ scores than HCs (42.77 ± 13.50 vs. 29.11 ± 4.25, t=9.697, p

Microresonator frequency comb-based high-speed data transmission provides a pathway towards augmented data capacity without increasing the number of laser sources. Their use with intensity-modulated direct detection modulation (IMDD) formats is especially pertinent in data center communications where minimizing cost, latency and complexity is paramount. This however implies that the same extent of digital signal processing techniques commonly used in coherent detection for the management of fiber impairments including chromatic dispersion are not available. With the proliferation of silicon photonics technologies in data center transceivers integrated dispersion compensation which can overcome fiber impairments would be of great merit. We demonstrate low power generation of the primary comb state in a silicon nitride microresonator and transmission of 25 Gb/s NRZ and 50 Gb/s PAM4 data over 20 km of single mode fiber. This represents the longest fiber reach demonstrated to date for the transmission of IMDD data using an integrated, microresonator frequency comb. An integrated, tunable grating device for dispersion compensation that reduces dispersion impairments after several fiber lengths generates significant improvements in the eye diagram, six orders of magnitude improvement in the bit-error rate and 14 dB improvement in the transmitter and dispersion eye closure quaternary values. Concurrently, doubling data transmission is demonstrated via polarization multiplexing a comb line and successful dispersion compensation of up to 20 km.

The utilization of synthetic aperture radar tomography (TomoSAR) technology for the three-dimensional imaging of urban areas has garnered significant attention. In the case of multi-pass spaceborne TomoSAR, eliminating the atmospheric phase screen (APS) is a critical step. At present, a two-tier network method is widely employed for APS removal from extensive regions. However, challenges persist in the construction of first-tier reference networks using the Delaunay triangulation and bridge reference network methods, such as low network coverage ratios and linear correlation problems associated with near-parallel bridges. Consequently, a notable portion of the inversion results for buildings or artificial structures are either absent or characterized by low accuracy. To fully harness the observational information from all small connecting networks, this study introduces an improved bridge reference network construction method based on a region-growing strategy. This method merges small subnetworks with surrounding reference networks using high-quality bridge connections to maximize the coverage of the largest reference network. To validate the feasibility and effectiveness of the proposed approach, 27 TerraSAR-X images, which were collected in Shenzhen, China were utilized to construct a reference network and estimate building heights. The results clearly indicate that the proposed method effectively overcomes the limitations of existing methods.

Background: The bone repair requires the bone scaffolds to meet various mechanical and biological requirements, which makes the design of bone scaffolds a challenging problem. Novel triply periodic minimal surface (TPMS)-based bone scaffolds were designed in this study to improve the mechanical and biological performances simultaneously.Methods: The novel bone scaffolds were designed by adding optimization-guided multi-functional pores to the original scaffolds, and finite element (FE) method was used to evaluate the performances of the novel scaffolds. In addition, the novel scaffolds were fabricated by additive manufacturing (AM) and mechanical experiments were performed to evaluate the performances.Results: The FE results demonstrated the improvement in performance: the elastic modulus reduced from 5.01 GPa (original scaffold) to 2.30 GPa (novel designed scaffold), resulting in lower stress shielding; the permeability increased from 8.58 × 10−9 m2 (original scaffold) to 5.14 × 10−8 m2 (novel designed scaffold), resulting in higher mass transport capacity.Conclusion: In summary, the novel TPMS scaffolds with multi-functional pores simultaneously improve the mechanical and biological performances, making them ideal candidates for bone repair. Furthermore, the novel scaffolds expanded the design domain of TPMS-based bone scaffolds, providing a promising new method for the design of high-performance bone scaffolds.

This study investigates the application of coherence and backscattering, derived from time-series Sentinel-1 synthetic aperture radar imagery of a crop season (18 scenes with a 12-day revisit cycle), for crop growth monitoring and classification in the agricultural region of Southwestern Ontario, Canada. To fulfill this goal, we initially analyze the temporal behavior of backscattering and coherence for a variety of crops to gain some insights for classification. Second, diverse combinations involving polarization channels, feature types, and image quantities for crop classification are analyzed. The deep analysis of temporal dynamics highlights a stronger correlation between the time-series curves of backscattering and crop growth in comparison to coherence. The VH backscattering and the VV coherence demonstrate a higher sensitivity to the variations in crop growth. The crop mapping results indicate that backscattering produces significantly higher accuracy of crop classification than coherence. Furthermore, the incorporation of coherence features with backscattering can enhance the accuracy, with VV making more pronounced contributions compared to VH. Notably, the most effective classification result is achieved through a scheme that integrates both backscattering coefficients of dual polarization (VV + VH) and the VV coherence, achieving a better overall accuracy of 95.33% and a kappa coefficient of 0.93. This study concludes that the crucial information provided by the temporal variations in backscattering and coherence to improve crop classification accuracy depends on both the polarization channel and crop type, with coherence playing a supplementary role. Our study consolidates the previous work and provides useful insights into the field of crop classification.

Nanchuan area in southeastern Chongqing is rich in normal pressure shale gas resources, which is an important area for SINOPEC's shale gas exploration and development. Due to the complex geological conditions and imperfect engineering technology, the overall efficiency of drilling acceleration and efficiency improvement in this area can not meet the requirements for large-scale benefit-based development of normal pressure shale gas. Therefore, Yangye 54-3HF well in Yangchungou block in this area is selected as the first normal pressure shale gas demonstration well of SINOPEC to research and form a regional optimal and fast drilling and completion demonstration technology series. On the basis of systematic analysis of regional drilling technology difficulties, combined with basic research on formation pressure resistance characteristics and formation pressure system, the demonstration well research systematically explores key drilling technologies such as shallow formation leakage technology, well structure optimization technology, accelerating tool optimization technology, trajectory control and orientation technology, low-density strong plugging oil-based drilling fluid technology, and optimal fast completion technology. A low-cost, optimal, and fast drilling demonstration technology system with the core of shallow formation prospecting, large-capacity clean water drilling, optimized well structure, domestic acceleration tools, low-density and strong plugging oil-based drilling fluid, integrated geological engineering orientation, and low-pressure wellbore fast cementing technology is formed. The drilling period of the demonstration well is 19.96 d, which is the shortest drilling period in 4 500 m well depth in China, and the ROP is 24.88 m/h, which is 141.79% higher than the fastest ROP of 10.29 m/h in the similar well depth in the same region. The rate of drilling in high-quality shale is 100%, and the cementing quality is excellent, which has played a good demonstration and leading role. After the promotion and application, various technical and economic indicators such as the regional ROP and drilling period have been significantly improved, speeding up the exploration and development process of normal pressure shale gas in Nanchuan area. The practice of normal pressure shale gas demonstration wells in Nanchuan area has shown that the efficient drilling and completion technology series formed by the demonstration well research can meet the requirements of drilling acceleration and efficiency improvement in horizontal wells of normal pressure shale gas, effectively promoting the four improvements in petroleum engineering to a new level, and laying a technical foundation for the construction of similar gas fields around the Sichuan Basin, and helping achieve greater progress in stabilizing oil and gas production, reducing costs, and improving efficiency in the upstream industry in China.

Defects in additive manufacturing processes are closely related to the mechanical and physical properties of the components. However, the extreme conditions of high temperatures, intense light, and powder during the manufacturing process present significant challenges for defect detection. Additionally, the high reflectivity of metallic components can cause pixels in image sensors to become overexposed, resulting in the loss of many defect signals. Thus, this paper mainly focuses on proposing an accurate inspection and super-resolution reconstruction method for additive manufactured defects based on Stokes vector and deep learning, where the Stokes vectors, polarization degree, and polarization angles of the inspected defects are effectively utilized to suppress the high reflectivity of metallic surfaces, enhance the contrast of defect regions, and highlight the boundaries of defects. Furthermore, a modified SRGAN model designated SRGAN-H is presented by employing an additional convolutional layer and activation functions, including Harswish and Tanh, to accelerate the convergence of the SRGAN-H network and improve the reconstruction of the additive manufactured defect region. The experiment results demonstrated that the SRGAN-H model outperformed SRGAN and traditional SR reconstruction algorithms in terms of the images of Stokes vectors, polarization degree, and polarization angles. For the scratch and hole test sets, the PSNR values were 33.405 and 31.159, respectively, and the SSIM values were 0.890 and 0.896, respectively. These results reflect the effectiveness of the SRGAN-H model in super-resolution reconstruction of scratch and hole images. For the scratch and hole images chosen in this study, the PSNR values of SRGAN-H for single image super-resolution reconstruction ranged from 31.86786 to 43.82374, higher than the results obtained by the pre-improvement SRGAN algorithm.

Additive manufacturing (AM) excels in engineering intricate shapes, pioneering functional components, and lightweight structures. Nevertheless, components fabricated through AM often manifest elevated residual stresses and a myriad of thermally induced micro-instabilities, including cracking, incomplete fusion, crazing, porosity, spheroidization, and inclusions. In response, this study proposed a sophisticated multi-sensing inspection system specifically tailored for the inspection of thermally induced micro-instabilities at the micro–nano scale. Simulation results substantiate that the modulation transfer function (MTF) values for each field of view in both visible and infrared optical channels surpass the benchmark of 0.3, ensuring imaging fidelity conducive to meticulous examination. Furthermore, the innovative system can discern and accurately capture data pertaining to thermally induced micro-instabilities across visible and infrared spectra, seamlessly integrating this information into a backend image processing system within operational parameters of a 380–450 mm distance and a 20–70 °C temperature range. Notably, the system’s design is harmoniously aligned with the requisites of processing and assembly, heralding a significant advancement in bolstering the inspection effect of thermally induced micro-instabilities for the AM component.

BackgroundObservational studies have shown that micronutrients can affect the occurrence of frailty. However, it is not clear whether there is a causal relationship between the two. This study aimed to explore the causal relationship between circulating micronutrient levels and frailty risk using a two-sample Mendelian randomization (TSMR) approach.MethodsWe gathered and screened instrumental variables (IVs) for six circulating micronutrients, including vitamin B12, vitamin B6, folate, vitamin C, vitamin D, and vitamin E, from published genome-wide association studies (GWAS) and the IEU OpenGWAS open database. Summary statistics for frailty were obtained from a GWAS meta-analysis, including the UK Biobank and TwinGene (N = 175,226). We performed two independent TSMR analyses and a meta-analysis based on the two independent MR estimates to assess the causal relationship between circulating micronutrientn and frailty.ResultsOur study found, no causal relationship between genetically predicted vitamin D (β = −0.059, p = 0.35), vitamin B6 (β = 0.006, p = 0.80), vitamin E (β = −0.011, p = 0.79), vitamin C (β = −0.044, p = 0.06), vitamin B12 (β = −0.027, p = 0.37), and folate (β = 0.029, p = 0.17), with frailty.ConclusionThis study showed that these six micronutrients did not reduce the risk of developing frailty. However, we think it is necessary further to investigate the relationship and mechanisms between micronutrients and frailty using methods such as randomized controlled trials.

ObjectiveThe aim of this study was to investigate the impact of early life adversity on cognitive function in patients with schizophrenia, with a focus on social cognition (SC).MethodsTwo groups of patients with schizophrenia were recruited and matched on sociodemographic and clinical characteristics. One group consisted of 32 patients with a history of childhood trauma (SCZ-ct), and the other group consisted of 30 patients without a history of childhood trauma (SCZ-nct). In addition, 39 healthy controls without a history of childhood trauma (HC-nct) were also recruited. The intelligence of the three groups was assessed using the Wechsler Abbreviated Scale of Intelligence (WAIS—RC) short version. The cognitive function evaluation was conducted using the MATRICS Consensus Cognitive Battery (MCCB), and early life adversity was measured using the Childhood Trauma Questionnaire-Short Form (CTQ) and Bullying Scale for Adults (BSA).ResultsPatients with schizophrenia endosed significantly higher scores on the CTQ (F=67.61, p

Abstract Additive manufacturing (AM) technology such as selective laser melting (SLM) often produces a high reflection phenomenon that makes defect detection and information extraction challenging. Meanwhile, it is essential to establish a characterization method for defect analysis to provide sufficient information for process diagnosis and optimization. However, there is still a lack of universal standards for the characterization of defects in SLM parts. In this study, a polarization-based imaging system was proposed, and a set of characterization parameters for SLM defects was established. The contrast, defect contour information, and high reflection suppression effect of the SLM part defects were analyzed. Comparative analysis was conducted on defect characterization parameters, including geometric and texture parameters. The experimental results demonstrated the effects of the polarization imaging system and verified the feasibility of the defect feature extraction and characterization method. The research work provides an effective solution for defect detection and helps to establish a universal standard for defect characterization in additive manufacturing.

Metal halide perovskites have shown unique advantages compared with traditional optoelectronic materials. Currently, perovskite films are commonly produced by either multi-step spin coating or vapor deposition techniques. However, both methods face challenges regarding large-scale production. Herein, we propose a straightforward in situ growth method for the fabrication of CsPbBr3 nanocrystal films. The films cover an area over 5.5 cm × 5.5 cm, with precise thickness control of a few microns and decent uniformity. Moreover, we demonstrate that the incorporation of magnesium ions into the perovskite enhances crystallization and effectively passivates surface defects, thereby further enhancing luminous efficiency. By integrating this approach with a silicon photodiode detector, we observe an increase in responsivity from 1.68 × 10−2 A/W to 3.72 × 10−2 A/W at a 365 nm ultraviolet wavelength.

The high-efficiency preparation of large-area microstructures of optical materials and precision graphic etching technology is one of the most important application directions in the atomic and near-atomic-scale manufacturing industry. Traditional focused ion beam (FIB) and reactive ion etching (RIE) methods have limitations in precision and efficiency, hindering their application in automated mass production. The pulsed ion beam (PIB) method addresses these issues by enhancing ion beam deflection to achieve high-resolution material removal on a macro scale, which can reach the equivalent removal resolution of 6.4 × 10−4 nm. Experiments were conducted on a quartz sample (10 × 10 × 1 mm) with a specific pattern mask using the custom PIB processing device. The surface morphology, etching depth, and roughness were measured post-process. The results demonstrated that precise control over cumulative sputtering time yielded well-defined patterns with expected average etching depths and surface roughness. This confirms the PIB technique’s potential for precise atomic depth image transfer and its suitability for industrial automation, offering a significant advancement in microfabrication technology.

A wavelet-transform-based highlight suppression method is presented, aiming at suppressing the highlights of single image with complex texture. The strategy involves the rough extraction of specular information, followed by extracting the high-frequency information in specular information based on multi-level wavelet transform to enhance the texture information in the original images by fusion strategy, and fusing with the same-level specular information to achieve the highlight suppression image. The experimental results demonstrate that the proposed method effectively removed large-area highlights while preserving texture details, and demonstrated the authenticity of the highlight estimation and the ‘lights off’ effect in the highlight-suppressed images. Overall, the method offers a feasibility for addressing the challenges of highlight suppression for visual detection image with rich texture and large-area highlights.

Post-processing based on HF etching has become a highly preferred technique in the fabrication of fused silica optical elements in various high-power laser systems. Previous studies have thoroughly examined and confirmed the elimination of fragments and contamination. However, limited attention has been paid to nano-sized chemical structural defects and secondary precursors that arise during the etching process. Therefore, in this paper, a set of fused silica samples are prepared and undergo the etching process under different parameters. Subsequently, an atomic force microscope, scanning electron microscope and fluorescence spectrometer are applied to analyze sample surfaces, and then an LIDT test based on the R-on-1 method is applied. The findings revealed that appropriate etching configurations will lead to certain LIDT improvement (from initial 7.22 J/cm2 to 10.76 J/cm2), and HF-based etching effectively suppresses chemical structural defects, while additional processes are recommended for the elimination of micron- to nano-sized secondary deposition contamination.

Forest height is of great significance for forest resource management and forest carbon sink estimation. Tomographic synthetic aperture radar (TomoSAR) technology provides an effective means for the accurate inversion of this parameter. Several multi-polarization synthetic aperture radar (SAR) images are generally required to obtain forest height. However, it is common that only a small number of single-polarization images can be acquired, due to the complexity of the systems and the limitations of the observation cycles, and there may be only one fully polarimetric image available. This means that it is impossible to use TomoSAR to estimate forest height over a wide area. Based on this, in this study, we combined polarimetric SAR (PolSAR) variables and single-polarization TomoSAR (SP-TomoSAR) features to estimate forest height for the first time. The image fusion was achieved through the use of six machine learning methods: light gradient-boosting machine (lightGBM), random forest (RF), extreme gradient boosting (XGBoost), gradient-boosted decision tree (GBDT), k-nearest neighbor (KNN), and support vector machine regression (SVR). To investigate the advantages of the proposed method, a small amount of SP-TomoSAR data with non-uniformly distributed baselines and one PolSAR image were acquired over the tropical rainforest of French Guiana. We then used H/A/alpha and Freeman-Durden decomposition methods to obtain the polarization features and applied the Capon algorithm to obtain the tomographic features. Four sets of comparative experiments were carried out, and the results confirmed that the combination of SP-TomoSAR and PolSAR can achieve an accurate estimation of forest height, and the estimation result of the HV tomographic features is better than that of the HH tomographic features. Moreover, after adding the polarization features, the estimation accuracy was clearly improved, compared to using only tomographic features, which suggests that PolSAR can provide important supplementary information for SP-TomoSAR. In addition, among the six machine learning algorithms, the RF algorithm has the highest estimation accuracy with a root mean square error (RMSE) of 5.14 m and an R of 0.83, while the lightGBM algorithm is significantly ahead of the others in terms of computational efficiency.

Land subsidence is a common geological hazard in urban areas. It can be caused by human activities such as land reclamation and subway construction. However, rapid urbanization can accelerate the progress of these activities. Therefore, spatial-temporal analysis of land subsidence can provide a guarantee for rapid urbanization progress. In this study, Shenzhen, one of the fastest urbanizing cities in China, is selected for continued land subsidence monitoring. We collected 153 Sentinel-1A images from December 2015 to July 2021 and utilized an interferometric point target analysis method to generate the land subsidence in Shenzhen. Additionally, we analyzed the relationship between land subsidence and typical urbanization progress: land reclamation, transportation network, and urban construction. The results show that land subsidence mostly occurs in the western reclamation area, with a maximum rate of −74.9 mm/a in Qianhai Bay. Areas with larger quaternary marine sediment thickness in the range of 10–20 m are more likely to experience subsidence. Obvious subsidence (

Nonlinear propagation in periodic media has been studied for decades, yielding demonstrations of numerous phenomena including strong temporal compression and slow light generation. Gap solitons, that propagate at frequencies inside the stopband, have been observed in optical fibres but have been elusive in photonic chips. In this manuscript, we investigate nonlinear pulse propagation in a chip-based nonlinear Bragg grating at frequencies inside the stopband and observe clear, unequivocal signatures of gap soliton propagation, including slow light, intensity-dependent transmission, intensity-dependent temporal delay and gap soliton compression. Our experiments which are performed in an on-chip ultra-silicon-rich nitride (USRN) Bragg grating with picosecond time scales, reveal slow light group velocity reduction to 35%–40% of the speed of light in vacuum, change in the temporal delay of 7 ps at low peak powers between 15.7 W–36.6 W, which is accompanied by up to 2.7× temporal compression of input pulses. Theoretical calculations using the nonlinear coupled mode equations confirm the observations of intensity-dependent temporal delay. Of fundamental importance, this demonstration opens up on-chip platforms for novel experimental studies of gap solitons as the basis of all-optical buffers, delay lines and optical storage.

The underlying topography and forest height play an indispensable role in many fields, including geomorphology, civil engineering construction, forest investigation, and the modeling of natural disasters. As a new microwave remote sensing technology with three-dimensional imaging capability, synthetic aperture radar (SAR) tomography (TomoSAR) has already been proven to be an important tool for underlying topography and forest height estimation. Many spectrum estimation methods have now been proposed for TomoSAR. However, most of the commonly used methods are susceptible to noise and inevitably produce sidelobes, resulting in a reduced accuracy for the inversion of forest structural parameters. In this paper, to solve this problem, a nonparametric spectrum estimation method with low sidelobes – the G-Pisarenko method – is introduced. This method performs a logarithmic operation on the covariance matrix to obtain the main scattering characteristics of the objects of interest while suppressing the noise as much as possible. The effectiveness of the proposed method is demonstrated by the use of both simulated data and P-band airborne SAR data from a tropical forest region in Gabon, Africa. The results show that the proposed method can reduce the sidelobes and improve the estimation accuracy for the underlying topography and forest height.

Abstract Soft electronics have attracted great interest owing to their potential applications in electronic skins, implanted devices, soft robotics, etc. Among the various soft materials, hydrogels are recognized as an ideal building block of soft electronics due to their tissue‐like physicochemical properties, abundant stimuli‐responses, and excellent mechanical compliances. Compared to elastomers, hydrogels containing large amounts of water exhibit better mechanical match to soft tissues and permeability to hydrophilic molecules. To date, most hydrogel‐based soft electronics (HSE) are facilely developed using a bulk conductive gel as the sensing unit, different from the elastomer‐based soft electronics with sophisticated integration of electronic elements. To advance their applications in engineering and biomedical fields, it is significant to devise hydrogel electronics with distributed sensing units. This Review summarizes the fabrication and applications of HSE, focusing on the multifunctional HSE with patterned conductive circuits and distributed sensing units. First, the fabrication of single‐functional soft electronics is briefly introduced with a bulk gel as the building block, including strain, temperature, chemical, and proximity sensors. Then, the approaches to integrating multiple sensing units into one hydrogel are summarized with examples of applications. Finally, perspectives are given on future directions and potential challenges in this field.

Abstract Preeclampsia is associated with the insufficient invasion of trophoblasts. NF-κB is a transcription factor in almost all mammalian cells and has been validated to be upregulated in the maternal circulation and placenta of women with preeclampsia. MiR-518a-5p is also overexpressed in pre-eclamptic placenta. The present study was designed to explore whether NF-κB can transcriptionally activate miR-518a-5p and investigate the influences of miR-518a-5p on the viability, apoptosis, migration, and invasion of HTR8/SVneo trophoblast. In situ hybridization and real time polymerase chain reaction were used to reveal miR-518a-5p expression in placenta tissues and HTR8/SVneo cells, respectively. Cell migration and invasion were detected using Transwell inserts. Our findings indicated that NF-κB p52, p50, and p65 can bind to miR-518a-5p gene promoter. MiR-518a-5p further influences the levels of p50 and p65 but not p52. HTR8/SVneo cell viability and apoptosis were not influenced by miR-518a-5p. However, miR-518a-5p represses the migratory/invasive capacities of HTR8/SVneo cell and decreased gelatinolytic activity of MMP2 and MMP9, which was reversed by an NF-κB inhibitor. To sum up, miR-518a-5p is induced by NF-κB and represses trophoblast cell migration and invasion by the NF-κB pathway.

Fringe projection is an important technology in three-dimensional measurement and target recognition. The measurement accuracy depends heavily on the calibration of the absolute phase and projector pixels. An easy-to-implement calibration method based on the Random Sample Consensus (RANSAC) algorithm is proposed to exterminate the phase error data and elevate the measurement accuracy in a fringe projection system. The reconstruction experiments of a double-sphere standard demonstrate that the uncertainties in radius and sphere-distance measurement are reduced to one thousandth of the measured value or even less, and the standard deviation in multiple measurements is restricted to within 50 μm. The measurement accuracy provided by the proposed RANSAC method can be improved by up to 44% compared with that provided by traditional least squared method (LSM). The proposed calibration method is easy and simple to implement, and it does not need additional hardware, but rather a calibration board.

Globally, the long-haul transmission of ultra-high bandwidth data is enabled through coherent communications. Driven by the rapid pace of growth in interconnectivity over the last decade, long-haul data transmission has reached capacities on the order of tens to hundreds of terabits per second, over fiber reaches which may span thousands of kilometers. Data center communications operate in regimes featuring shorter reaches and higher cost sensitivity. While integrated microresonator frequency combs are poised to revolutionize light sources used for high-speed data transmission over fiber, recent progress has focused largely on coherent detection schemes. Furthermore, though state-of-the-art intensity modulators are advancing in speed, it has not been demonstrated in the literature if microresonator-based comb lines can accommodate higher intensity modulated direction data (IMDD) line rates in tandem with these advancements. In this manuscript, we demonstrate the use of microresonator frequency combs pumped with a single laser for the transmission of high-speed IMDD data. We demonstrate error-free transmission of 30 Gbs−1 per comb non-return-to-zero data over fiber lengths of 6 km, as well as bit error rates under the forward error correction limit for propagation through 20 km of optical fiber. 60 Gbs−1 and 42 Gbs−1 pulse modulation amplitude 4 (PAM4) data modulated on each frequency comb line is further quantified to have a bit error rate under the forward error correction limit for fiber reaches of up to 6 km and 20 km respectively. The results showcase CMOS-compatible microresonator frequency comb modulated using IMDD formats as a promising technology for high-speed transmission in the data center transceiver industry.

Arsenic (As) is one of the most toxic metalloids that possess many forms. As is constantly migrating from abandoned mining area to the surrounding environment in both oxidation and reducing conditions, threatening human health and ecological safety. The biogeochemical reaction of As included oxidation, reduction, methylation, and demethylation, which is closely associated with microbial metabolisms. The study of the geochemical behavior of arsenic in mining areas and the microbial remediation of arsenic pollution have great potential and are hot spots for the prevention and remediation of arsenic pollution. In this study, we review the distribution and migration of arsenic in the mining area, focus on the geochemical cycle of arsenic under the action of microorganisms, and summarize the factors influencing the biogeochemical cycle of arsenic, and strategies for arsenic pollution in mining areas are also discussed. Finally, the problems of the risk control strategies and the future development direction are prospected.

Parthenolide (PTL or PAR) was first isolated from Magnolia grandiflora and identified as a small molecule cancer inhibitor. PTL has the chemical structure of C15H20O3 with characteristics of sesquiterpene lactones and exhibits the biological property of inhibiting DNA biosynthesis of cancer cells. In this review, we summarise the recent research progress of medicinal PTL, including the therapeutic effects on skeletal diseases, cancers, and inflammation-induced cytokine storm. Mechanistic investigations reveal that PTL predominantly inhibits NF-κB activation and other signalling pathways, such as reactive oxygen species. As an inhibitor of NF-κB, PTL appears to inhibit several cytokines, including RANKL, TNF-α, IL-1β, together with LPS induced activation of NF-κB and NF-κB -mediated specific gene expression such as IL-1β, TNF-α, COX-2, iNOS, IL-8, MCP-1, RANTES, ICAM-1, VCAM-1. It is also proposed that PTL could inhibit cytokine storms or hypercytokinemia triggered by COVID-19 via blocking the activation of NF-κB signalling. Understanding the pharmacologic properties of PTL will assist us in developing its therapeutic application for medical conditions, including arthritis, osteolysis, periodontal disease, cancers, and COVID-19-related disease.

Existing pavement defect detection models face challenges in balancing detection accuracy and speed while being constrained by large parameter sizes, hindering deployment on edge terminal devices with limited computing resources. To address these issues, this paper proposes a lightweight pavement defect detection model based on an improved YOLOv7 architecture. The model introduces four key enhancements: first, the incorporation of the SPPCSPC_Group grouped space pyramid pooling module to reduce the parameter load and computational complexity; second, the utilization of the K-means clustering algorithm for generating anchors, accelerating model convergence; third, the integration of the Ghost Conv module, enhancing feature extraction while minimizing the parameters and calculations; fourth, introduction of the CBAM convolution module to enrich the semantic information in the last layer of the backbone network. The experimental results demonstrate that the improved model achieved an average accuracy of 91%, and the accuracy in detecting broken plates and repaired models increased by 9% and 8%, respectively, compared to the original model. Moreover, the improved model exhibited reductions of 14.4% and 29.3% in the calculations and parameters, respectively, and a 29.1% decrease in the model size, resulting in an impressive 80 FPS (frames per second). The enhanced YOLOv7 successfully balances parameter reduction and computation while maintaining high accuracy, making it a more suitable choice for pavement defect detection compared with other algorithms.

We demonstrate a complementary metal–oxide–semiconductor (CMOS)-compatible optical parametric Bragg amplifier on an ultra-silicon-rich nitride chip. The amplifier design incorporates advantageous group index properties in a nonlinear Bragg grating to circumvent phase matching limitations arising from the bulk material and waveguide dispersion. The grating structure further augments the effective nonlinear parameter of 800 W−1/m, considerably lowering the power required for the observation of strong parametric gain. On/off optical parametric gain of 20 dB is achieved using a low peak power of 1.6 W, in good agreement with numerical calculations. This represents a 7 dB improvement in the parametric gain compared to the absence of grating enhancement which is attributed to the Bragg grating induced superior phase matching.

Danio roseus, collected from Gadu River in Yingjiang area, Yunnan Province, China, had been sequenced on Illumina HiSeq platform with 16523 bp in length, which included 37 genes encoding 13 proteins-coding genes (PCGs), 22 tRNAs, 2 rRNAs and a displacement loop region. The proportion of nucleotides in mitochondrial genome was T (28.7%), C (23.2%), A (32.3%), G (15.8%) with an AT bias of 61%. Maximum-Likelihood phylogenetic tree was reconstructed using concatenated mitochondrial protein-coding genes of D. roseus and other 12 fishes. The result of phylogenetic analysis supported the consanguineous relationship among D. roseus, D. rerio, D. nigrofasciatus and D. dangila.

Fused silica has become the preferred optical material in the field of inertial confinement fusion (ICF) due to its excellent performance; however, these costly optical elements are vulnerable, and their manufacture is time-consuming. Therefore, the restoration of laser-induced damage for these optical elements is of great value. To restrain the post-restoration raised rim problem in the CO2 laser repair process to improve the restoration quality, the separate influences of key parameters of laser power, irradiation duration, and laser beam diameter on post-restoration pit morphology are compared in combined simulation and experimental studies. An optimized, patterned CO2 laser strategy is proposed and verified; the results indicate that, with the strategy, the rim height decreases from 2.6 μm to 1.52 μm, and maximal photo thermal absorption is decreased from 784.2 PPM to 209.43 PPM.

Abstract Inhibition of return (IOR) refers to the slower response to targets appearing on the same side as the cue (valid locations) than to targets appearing on the opposite side as the cue (invalid locations). Previous behaviour studies have found that the visual IOR is larger than the audiovisual IOR when focusing on both visual and auditory modalities. Utilising the high temporal resolution of the event-related potential (ERP) technique we explored the possible neural correlates with the behaviour IOR difference between visual and audiovisual targets. The behavioural results revealed that the visual IOR was larger than the audiovisual IOR. The ERP results showed that the visual IOR effect was generated from the P1 and N2 components, while the audiovisual IOR effect was derived only from the P3 component. Multisensory integration (MSI) of audiovisual targets occurred on the P1, N1 and P3 components, which may offset the reduced perceptual processing due to audiovisual IOR. The results of early and late differences in the neural processing of the visual IOR and audiovisual IOR imply that the two target types may have different inhibitory orientation mechanisms.

Fringe projection profilometry (FPP) has been broadly applied in three-dimensional (3D) measurements, but the existing multi-shot methods, which mostly utilize phase-shifting techniques, are heavily affected by the disturbance of vibration and cannot be used in dynamic scenes. In this work, a single-shot 3D measurement method using a deep neural network named the Fringe Analysis Network (FrANet) is proposed. The FrANet is composed of a phase retrieval subnetwork, phase unwrapping subnetwork, and refinement subnetwork. The combination of multiple subnetworks can help to recover long-range information that is missing for a single U-Net. A two-stage training strategy in which the FrANet network is pre-trained using fringe pattern reprojection and fine-tuned using ground truth phase maps is designed. Such a training strategy lowers the number of ground truth phase maps in the data set, saves time during data collection, and maintains the accuracy of supervised methods in real-world setups. Experimental studies were carried out on a setup FPP system. In the test set, the mean absolute error (MAE) of the refined absolute phase maps was 0.0114 rad, and the root mean square error (RMSE) of the 3D reconstruction results was 0.67 mm. The accuracy of the proposed method in dynamic scenes was evaluated by measuring moving standard spheres. The measurement of the sphere diameter maintained a high accuracy of 84 μm at a speed of 0.759 m/s. Two-stage training only requires 8800 fringe images in data acquisition, while supervised methods require 96,000 fringe images for the same number of iterations. Ablation studies verified the effectiveness of two training stages and three subnetworks. The proposed method achieved accurate single-shot 3D measurements comparable to those obtained using supervised methods and has a high data efficiency. This enables the accurate 3D shape measurement of moving or vibrating objects in industrial manufacturing and allows for further exploration of network architecture and training strategy with few training samples for single-shot 3D measurement.

ObjectiveSchizophrenia is a mental disorder that is characterized by progressive cognitive impairment. Objective measures of cognitive function may provide reliable neurobiomarkers for patients with schizophrenia. The goal of the current work is to explore the correlation between resting theta power and cognitive performance in patients with schizophrenia.MethodsTwenty-two patients with schizophrenia and 23 age-, sex-, and education-matched healthy controls were included in this study. The MATRICS Consensus Cognitive Battery (MCCB) was used for cognitive evaluation and the Positive and Negative Syndrome Scale (PANSS) for evaluation of clinical symptoms. EEGs were acquired in the resting state with closed and opened eyes. Between the two groups, we compared the relative theta power and examined their relationship with cognitive performance.ResultsCompared to healthy controls, patients with schizophrenia showed significantly higher theta power, both with eyes closed and open (P < 0.05). When the eyes were open, negative correlations were found in patients with schizophrenia between theta power in the central and parietal regions with processing speed scores, and between the theta power of the Pz electrode and verbal learning and reasoning and problem-solving scores (r ≥ −0.446). In the control group, theta power over the Fz electrode was negatively correlated with processing speed (r = −0.435).ConclusionsOur findings showed that theta activity increased in certain brain regions during resting state in schizophrenia. Negative associations between resting theta power (increased) over the parietal-occipital regions with MCCB domains scores (decreased) suggest that altered theta activity can be used as a neurobiological indicator to predict cognitive performance.

Emotion is a kind of micro foundation that can affect human behaviors even in the digital era. Emotional intelligence (EI) is an important psychological factor that affects the growth and development of organizations from the view of emotion. Based on current bodies of literature, a comprehensive review of EI can contribute to its theory development in organization research and facilitate EI research burgeoning. We visualize the landscape of EI by analyzing 1,996 articles with CiteSpace their concepts, dimensions, and measurement. We propose two specific mechanisms, which clarify how individuals with high EI use emotional information to influence themselves and others. Following this, we develop a theoretical framework of EI at levels of individual, team, and organization. Finally, future directions and research agenda are addressed. This research contributes to the literature of EI and provides practical insight for practitioners.

Our research aimed to investigate the effectiveness of auditory, visual, and audiovisual warning signals for capturing the attention of the pilot, and how stimulus onset asynchronies (SOA) in audiovisual stimuli affect pilots perceiving the bimodal warning signals under different perceptual load conditions. In experiment 1 of the low perceptual load condition, participants discriminated the location (right vs. left) of visual targets preceded by five different types of warning signals. In experiment 2 of high perceptual load, participants completed the location task identical to a low load condition and a digit detection task in a rapid serial visual presentation (RSVP) stream. The main effect of warning signals in two experiments showed that visual and auditory cues presented simultaneously (AV) could effectively and efficiently arouse the attention of the pilots in high and low load conditions. Specifically, auditory (A), AV, and visual preceding auditory stimulus by 100 ms (VA100) increased the spatial orientation to a valid position in low load conditions. With the increase in visual perceptual load, auditory preceding the visual stimulus by 100 ms (AV100) and A warning signals had stronger spatial orientation. The results are expected to theoretically support the optimization design of the cockpit display interface, contributing to immediate flight crew awareness.

In this work, as-cast Mg–Ni–Y alloys were proposed to develop a feasible material for fracturing balls, and their mechanical performance and corrosion behavior were systematically investigated. Long period stacking order (LPSO) phase was firstly introduced to improve both the mechanical properties and degradation rate of magnesium alloys. With the increase of LPSO phase, the compressive strength was improved significantly, while the elongation of the alloys decreased owing to the relatively brittle nature of LPSO phase. Due to the higher corrosion potential of LPSO phase, the LPSO phase can accelerate the corrosion process by providing more micro-couples. However, the LPSO phase would serve as the corrosion barrier between the corrosion medium and the matrix when the contents of LPSO phase are too high in Mg92.5Ni3Y4.5 and Mg87.5Ni5Y7.5 alloys. As-cast Mg97.5Ni1Y1.5 alloy with satisfactory mechanical properties and rapid degradation rate was successfully developed, exhibiting a high degradation rate of 6675 mm/a (93 °C) in 3 wt.% KCl solution and a favorable ultimate compressive strength of 410 MPa. The degradation rate of Mg97.5Ni1Y1.5 alloy is 2–5 times of the current commercial magnesium alloy fracturing materials. Keywords: Mg–Ni–Y magnesium alloys, Fracturing ball, LPSO phase, Degradation rate, Mechanical properties

To clarify how micro-LED far-field light distributions differ from Lambertian distributions owing to small-sized-structure effects, the light distribution of a micro-LED was simulated via the ray-tracing method in this study. Specifically, considering material absorption, far-field light distribution, and light-output efficiency, we studied micro-LEDs as a function of size. We found that the light distribution is the most uniform and the efficiency is the highest when the size is the smallest under certain conditions. Under other conditions, with increasing sapphire size, the luminous efficiency first increases and then decreases. The luminous efficiency is the highest when the thickness is 30 µm. Under certain other conditions, as the diameter of the micro-sphere structure on the sapphire increases, the luminous efficiency first increases and then decreases.

The orbit error caused by the inaccuracy of the orbit state vector can lead to fringes in differential interferograms, which can impede the estimation of deformation in differential SAR interferometry (DInSAR) applications. Usually, a set of polynomial coefficients for an entire SAR image is obtained for orbit error removal. However, the orbit error plane is influenced by overfitting in the case that the SAR satellites do not have a precise orbit. In this paper, a patch-based polynomial method is proposed to fit the orbit error plane. The new method divides an SAR image into several overlapping patches in the azimuth and range directions. Every patch obtains its own polynomial coefficients, and an iterative least-square method is used to mosaic the orbit plane. This method is tested and validated via a simulated dataset and then applied to ALOS1/2 PALSAR and Sentinel-1A datasets. The accuracy of deformation is evaluated by in situ GPS datasets. The results show that the patch-based method can fit the orbit phase plane more accurately than the traditional polynomial model with millimeter-level displacement improvement, especially in the margin areas of ALOS1/2 and for the wide-coverage Sentinel-1A datasets. Moreover, in the MTInSAR parameter calculations, the new method improves the accuracy of mean velocity calculations for ALOS1 time series, with a reduction of RMSE from 4.47 mm/yr to 3.17 mm/yr. Additionally, the new method reduces the spatial correlation of the residual topographic phase, with a mean value reduction from 0.32 m to 0.13 m.

Previous behavioral studies have found that inhibition of return decreases the audiovisual integration, while the underlying neural mechanisms are unknown. The current work utilized the high temporal resolution of event-related potentials (ERPs) to investigate how audiovisual integration would be modulated by inhibition of return. We employed the cue-target paradigm and manipulated the target type and cue validity. Participants were required to perform the task of detection of visual (V), auditory (A), or audiovisual (AV) targets shown in the identical (valid cue) or opposed (invalid cue) side to be the preceding exogenous cue. The neural activities between AV targets and the sum of the A and V targets were compared, and their differences were calculated to present the audiovisual integration effect in different cue validity conditions (valid, invalid). The ERPs results showed that a significant super-additive audiovisual integration effect was observed on the P70 (60∼90 ms, frontal-central) only under the invalid cue condition. The significant audiovisual integration effects were observed on the N1 or P2 components (N1, 120∼180 ms, frontal-central-parietal; P2, 200∼260 ms, frontal-central-parietal) in both valid cue as well as invalid cue condition. And there were no significant differences on the later components between invalid cue and valid cue. The result offers the first neural demonstration that inhibition of return modulates the early audiovisual integration process.

Multi-sensor defect detection technology is a research hotspot for monitoring the powder bed fusion (PBF) processes, of which the quality of the captured defect images and the detection capability is the vital issue. Thus, in this study, we utilize visible information as well as infrared imaging to detect the defects in PBF parts that conventional optical inspection technologies cannot easily detect. A multi-source image acquisition system was designed to simultaneously acquire brightness intensity and infrared intensity. Then, a multi-sensor image fusion method based on finite discrete shearlet transform (FDST), multi-scale sequential toggle operator (MSSTO), and an improved pulse-coupled neural networks (PCNN) framework were proposed to fuse information in the visible and infrared spectra to detect defects in challenging conditions. The image fusion performance of the proposed method was evaluated with different indices and compared with other fusion algorithms. The experimental results show that the proposed method achieves satisfactory performance in terms of the averaged information entropy, average gradient, spatial frequency, standard deviation, peak signal-to-noise ratio, and structural similarity, which are 7.979, 0.0405, 29.836, 76.454, 20.078 and 0.748, respectively. Furthermore, the comparison experiments indicate that the proposed method can effectively improve image contrast and richness, enhance the display of image edge contour and texture information, and also retain and fuse the main information in the source image. The research provides a potential solution for defect information fusion and characterization analysis in multi-sensor detection systems in the PBF process.

Triply periodic minimal surface (TPMS) is identified as a suitable model for designing porous structures. Gyroid cellular structure (GCS) is the most widely studied type of TPMS structure. The majority of previous studies on GCS have focused on its isotropic structure. However, as a potential candidate for bone repair, anisotropic structures need to be considered. This study presented a strategy to control the anisotropy of GCS by changing its geometrical parameters. The finite element method was subsequently applied to determine the elastic response of anisotropic GCS under compression. The degree of anisotropic (DA) of GCS was evaluated in terms of the ratio of equivalent elastic modulus in vertical and horizontal directions. Within the parameters considered, the DA of GCS varied from 0.17 to 3.6, as compared with 0.2 to 4 for human bones. The main factors affecting the anisotropic elastic response of GCS were structure anisotropy, porosity, and loading direction. The elastic modulus of the anisotropic GCS was in the range 0.03 to 5.6GPa for titanium alloy, as compared with 0.1 to 4.5GPa for human trabecular bone. Combining the porosity and anisotropic models of GCS can offer a scaffold that matches closely the human bone mechanical environment.

Abstract Background In the pig production industry, artificial insemination (AI) plays an important role in enlarging the beneficial impact of elite boars. Understanding the genetic architecture and detecting genetic markers associated with semen traits can help in improving genetic selection for such traits and accelerate genetic progress. In this study, we utilized a weighted single-step genome-wide association study (wssGWAS) procedure to detect genetic regions and further candidate genes associated with semen traits in a Duroc boar population. Overall, the full pedigree consists of 5284 pigs (12 generations), of which 2693 boars have semen data (143,113 ejaculations) and 1733 pigs were genotyped with 50 K single nucleotide polymorphism (SNP) array. Results Results show that the most significant genetic regions (0.4 Mb windows) explained approximately 2%~ 6% of the total genetic variances for the studied traits. Totally, the identified significant windows (windows explaining more than 1% of total genetic variances) explained 28.29, 35.31, 41.98, and 20.60% of genetic variances (not phenotypic variance) for number of sperm cells, sperm motility, sperm progressive motility, and total morphological abnormalities, respectively. Several genes that have been previously reported to be associated with mammal spermiogenesis, testes functioning, and male fertility were detected and treated as candidate genes for the traits of interest: Number of sperm cells, TDRD5, QSOX1, BLK, TIMP3, THRA, CSF3, and ZPBP1; Sperm motility, PPP2R2B, NEK2, NDRG, ADAM7, SKP2, and RNASET2; Sperm progressive motility, SH2B1, BLK, LAMB1, VPS4A, SPAG9, LCN2, and DNM1; Total morphological abnormalities, GHR, SELENOP, SLC16A5, SLC9A3R1, and DNAI2. Conclusions In conclusion, candidate genes associated with Duroc boars’ semen traits, including the number of sperm cells, sperm motility, sperm progressive motility, and total morphological abnormalities, were identified using wssGWAS. KEGG and GO enrichment analysis indicate that the identified candidate genes were enriched in biological processes and functional terms may be involved into spermiogenesis, testes functioning, and male fertility.

Copper tailings are potential resources rich in iron minerals and their long-term stockpiling not only cause resource waste but also bring serious pressure to the ecological environment. Therefore, the resource utilization of copper tailings has attracted considerable attention and becomes the key to the sustainable development of the copper industry. In this study, the technology of the selective reduction of iron from copper tailings at low temperature using coal and recovery of iron from reduction pellets using magnetic separation was proposed. The effects of several factors, such as reduction temperature, reducing agent dosage, reduction time, and activator dosage, on the selective reduction and recovery of iron from copper tailings were investigated. The following optimum process conditions are determined through single-factor experiments: the reduction temperature is 1200℃, the reducing agent dosage is 25% of the mass of copper tailings, the reduction time is 2 h, and the activator dosage is 5% of the mass of copper tailings. Under the optimum process conditions, the iron mass fraction of the magnetic concentrate exceeds 90%, and the iron recovery rate is greater than 95%. The composition and structure of copper tailings, reduction pellets, and magnetic ores were determined via X-ray diffraction, optical microscopy, and scanning electron microscopy. Moreover, the mechanism of mineral phase reduction and metal phase generation/merging was revealed. The results show that increase in temperature is beneficial for the reduction, merging, and growth of the metal phase. Merging the metal particles becomes common by increasing the reducing agent dosage. Prolonging the reduction time promotes the merging of metal particles and reduction of fayalite. The activator promotes the diffusion and merging of metal particles. The merging and growth of metal particles promote the increase in particle size. The amount of slag wrapped by coarse metal particles in the magnetic concentrate is relatively small in the magnetic separation process, and the iron grade of the magnetic concentrate is significantly improved.

In light of the serious environmental pollution caused by the conventional roasting processes and the corresponding low comprehensive utilization of rubidium resources, a novel acid leaching and solvent extraction process was developed to extract rubidium from rubidium mica ore.The effects of leaching temperature, sulfuric acid concentration, and time on the leaching of rubidium were investigated, and the phase transformations during the leaching were analyzed through X-ray diffraction(XRD), scanning electron microscope(SEM), and energy dispersive spectrometry(EDS).The experimental results show that the optimum conditions of acid leaching for rubidium mica ore are as follows: leaching temperature of 250 ℃, H2SO4 concentration of 200 g·L－1, and leaching time of 1 h.Under these conditions, the leaching ratio of rubidium increases up to 85. 2%.The XRD patterns of the raw ore indicate that quartz, biotite, muscovite, orthoclase, and albite are the major phases.Further SEM-EDS analysis shows that the Rb is scatted in biotite and muscovite in the form of isomorphism.Furthermore, the main reaction in the leaching process was the dissolution of the rubidium-rich micas.The countercurrent extraction experiment was conducted under the following conditions: extractant concentration of 1 mol·L－1, phase ratio(O/A)of 3:1, and extraction stage 3.The concentration of rubidium in the raffinate was 0. 003 g·L－1, and the extraction ratio of rubidium was 98%.After performing the 2-stage countercurrent stripping with 1 mol·L－1 HCl at a phase ratio(O/A)of 4:1, the stripping ratio of rubidium reached 99%.Silica white was prepared via alkali melting leaching residue and neutralization precipitation; thus, the comprehensive utilization of rubidium resource was achieved.XRD and Fourier transform infrared spectroscopy were used to characterize the silica white product.The corresponding results show that the product comprises hydrated silica, thus meeting the characteristics of the amorphous silica white.Finally, the chemical quantitative analysis results show that the silica white product comprises 91. 65% of SiO2, which is in accordance with the national chemical industry standard.

A scheme for designing a novel optical receiving antenna is proposed to extend the field of view, receive higher power, and reduce the received-energy spot area for indoor visible light communication (VLC). ProE is used to model the antenna, while TracePro and Matlab are employed for simulations. Firstly, the lens wall of a compound parabolic concentrator with a certain rotation angle and thickness is obtained through rotating the parabolic reflector cross-section reference curve. Furthermore, a novel optical receiving antenna is designed in combination with the advantages of the lens-walled CPC and the spherical lens. Then, the Taguchi methodology and ANOVA technique are utilized to optimize the structure parameters of the receiving antenna. Finally, an indoor VLC system model is established and the channel performance is analyzed. Simulation results show that the designed antenna achieves the following performances: optical gain of 21.53, field of view of 45°, and spot size of 3 mm. The received power is 9.5532 dBm, and the SNR is 86.2526 dB, which further confirms that the designed optical receiving antenna is suitable for indoor VLC systems.

Synthetic aperture radar (SAR) tomography (TomoSAR) is a powerful tool for the three-dimensional (3D) reconstruction of buildings in urban areas. At present, the compressed sensing (CS) technique has been widely used in the TomoSAR inversion of urban areas because of the sparsity of the backscattering power of buildings along the elevation direction. However, this algorithm discretizes the elevation and assumes that the scatterers are located on predetermined finite grids. In fact, scatterers can lie anywhere in the elevation direction, regardless of grid point constraints. The phenomenon of scatterer positioning errors due to elevation discretization is called the off-grid effect, which will affect the height estimation accuracy of TomoSAR. To overcome this problem, we proposed a TomoSAR reconstruction algorithm based on atomic norm minimization (Tomo-ANM) in this paper. Tomo-ANM employs ANM, a continuous compressed sensing technique, to obtain scatterer positions on the continuous dictionary, thus eliminating the off-grid effect. Baseline compensation is necessary to obtain the data of virtual uniform baselines or the samples of uniform data during preprocessing. A fast realization of ANM, IVDST, is utilized to accelerate the process. Tomo-ANM was tested through simulation experiments, and the results confirmed the validity of eliminating the influence of off-grid effects and exhibited an improved location accuracy and detection rate in less time compared with the on-grid TomoSAR algorithm SL1MMER. Real data experiments based on eight staring spotlight TerraSAR-X images showed that Tomo-ANM can improve the accuracy of building height estimation by 4.83% relative to its real height.

Crop identification and classification are of great significance to agricultural land use management. The physically constrained general model-based decomposition (PCGMD) has proven to be a promising method in comparison with the typical four-component decomposition methods in scattering mechanism interpretation and identifying vegetation types. However, the robustness of PCGMD requires further investigation from the perspective of final applications. This paper aims to validate the efficiency of the PCGMD method on crop classification for the first time. Seven C-band time-series RADARSAT-2 images were exploited, covering the entire growing season over an agricultural region near London, Ontario, Canada. Firstly, the response and temporal evolution of the four scattering components obtained by PCGMD were analyzed. Then, a forward selection approach was applied to achieve the highest classification accuracy by searching an optimum combination of multi-temporal SAR data with the random forest (RF) algorithm. For comparison, the general model-based decomposition method (GMD), the original and its three improved Yamaguchi four-component decomposition approaches (Y4O, Y4R, S4R, G4U), were used in all tests. The results reveal that the PCGMD method is highly sensitive to seasonal crop changes and matches well with the real physical characteristics of the crops. Among all test methods used, the PCGMD method using six images obtained the optimum classification performance, reaching an overall accuracy of 91.83%.