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Staggered synthetic aperture radar (SAR) can effectively stagger range blind areas by periodically changing the pulse repetition interval (PRI), to achieve continuous imaging with an ultrawide swath. In conventional staggered SAR, azimuth samples are nonuniformly distributed due to the variable PRI, and complex resampling processing, such as best linear unbiased (BLU) interpolation and multichannel reconstruction processing, is required. In this article, a strict rule of PRI variation and phase center adjustment (PCA) is proposed for staggered SAR, to solve the problem of nonuniform azimuth sampling. In the proposed joint strategy of PRI variation and PCA, the relevant parameters for PCA are first determined. Then, the PRI sequence is designed according to PCA parameters to stagger blind ranges. Finally, the PCA rule is designed according to the designed PRI sequence and PCA parameters. During the data acquisition interval, the effective phase center is periodically adjusted pulse by pulse according to this rule, making the azimuth samples totally uniformly distributed. In addition, the discontinuously distributed missing samples can be estimated by signal estimation approaches. With the proposed joint rule of PRI variation and PCA, the emergence of false targets in imaging results can be avoided, and the complex resampling processing can be relieved to reduce the computational complexity. Simulation experiments on imaging results verify the advantages of this strategy.

With its special, arch-shaped array structure, a frequency diverse arc array (FDAA) can perform beam scanning in 360 degrees in azimuth and in arbitrary ranges by selectively activating array elements in different positions, utilizing array element phase compensation, and adopting a frequency offset design. In this paper, a beampattern synthesis and optimization method for FDDA using the virtual array element based on the geometric configuration of FDDA is proposed. First, the position of the virtual array element is determined by the direction of the target, and then activated array elements are selected. Afterwards, the frequency offset of each array element is set up on the equiphase surface to obtain the dot-shaped beampattern. Finally, amplitude weighting is introduced to suppress the increased sidelobe level of the dot-shaped beampattern, which is caused by inverse density weighting of the arch-shaped array structure. Simulation results validate the proposed method for beampattern synthesis and optimization in FDAA.

Severe skin wound healing is mainly hindered by bacterial infection and uncontrolled inflammatory reaction. As a wound dressing, multifunctional hydrogel is expected to offer the potential possibility for overcoming current barriers in wound therapeutics. Herein, a natural drug molecule (glycyrrhizic acid, GA) and metal ion (Fe

A standardized reference method is needed to accurately and precisely measure urine-formed elements (UFEs; red blood cells [RBCs], white blood cells [WBCs], and squamous epithelial cells [sECs]). We compared the results from a standard method with those from an automated analyzer. Trained technicians used standardized bright-field microscopy of fresh non-centrifuged urine samples, and disposable 1 µl chambers. Fifteen experienced technicians from 5 hospitals (3 per hospital) each performed 6 manual counts of 10 different native urine samples using a manual chamber and standard methods. The sEC counts were at least 50/µL, and the coefficient of variation (CV) was less than 14%; the RBC and WBC counts were at least 200/µL and the CVs were less than 7%. The same samples were also analyzed 6 times using automated analyzers. The means, CVs, and biases were determined. The median CVs for the manual measurements were 6.4% (WBCs), 6.6% (RBCs), and 12.7% (sECs). The CVs of the automated analyzer were 4.7% (WBCs), 5.6% (RBCs), and 9.2% (sECs). Biases between the automated and manual methods were -2.9% to 5.0%(WBCs), -0.8% to 8.8% (RBCs) and -2.8% to 9.4% (sECs). The count mean values and expanded uncertainties of these counts were (224.5 ± 15.0) cells/µL, (234.2 ± 16.2) cells/µL, and (61.5 ± 7.9) cells/µL, respectively. The standardized manual method for measuring UFEs had high precision and accuracy, making it a suitable reference method. Use of this reference method to calibrate an automated analyzer improved the accuracy of automated analysis.

The performance of moving target detection for airborne radar depends on estimation accuracy of clutter covariance matrix. In nonhomogeneous clutter environments, dense interference will impact the estimation accuracy of the clutter covariance matrix, resulting in failure of moving target detection. To cope with this problem, this paper proposes a moving target detection algorithm for airborne radar based on fuzzy mathematics and signal sparse recovery technology. The proposed algorithm calculates the sparse recovery coefficient vectors of training snapshots firstly, and then uses the appropriate membership function to process the matrix which is consist of these vectors. The clutter components in coefficient vector are selected according to membership function, and clutter covariance matrix are estimation subsequently. By comparing and analyzing clutter space-time spectrum, clutter suppression performance, and moving target detection performance, it can be found that the proposed algorithm improves the moving target detection performance. Moreover, the proposed algorithm only needs few training snapshots, is robust to the suppression of dense interference.

Background This study assessed the homogeneity and stability of control materials used in external quality assessment (EQA) of four coagulation tests, aiming to verify that these materials meet clinical testing requirements and to provide an evidence base for future improvement of laboratory coagulation test quality. Methods The homogeneity and stability of control materials were assessed according to the relevant guidance. Homogeneity assessment involved 10 vials of samples obtained from 2 batches (each vial tested twice). The homogeneity of control materials in four coagulation tests was assessed using one-way analysis of variance, with standard deviation of uniformity (Ss) 0.3 σ as an assessment criterion. Stability assessment involved two vials of sam-ples obtained from two batches (each vial tested twice). The stability of control materials was assessed at cold storage, room temperature, temperature of 37°C. Reconstitution stability of control materials placed in cold storage and at room temperature, and long-term stability of reconstituted control materials stored frozen (-20°C and -80°C) were observed. Linear regression analysis was performed to assess long-term stability. Results The Ss values of EQA control materials for four coagulation tests were PT L1 Ss = 0.084, PT L2 Ss = 0.889, APTT L1 Ss = 0.164, APTT L2 Ss = 0.223, Fbg L1 Ss = 6.256, Fbg L2 Ss = 2.251, TT L1 Ss = 0.552, TT L2 Ss = 0.3111. PT, APTT, Fbg, and TT were associated with the standard deviation of uniformity values of 0.3 σ. Non-reconstituted samples were observed at 37°C for 2 hours and 4 hours, and at room temperature for 1 day. Reconstituted samples were observed when stored at 4°C for 4 hours and 8 hours, at room temperature for 4 hours, and at -20°C and -80°C for 6 months. Instability of reconstituted samples was observed in PT and APTT tests at 4°C for 8 hours and at -20°C for 5 months. Conclusions EQA control materials presented with satisfactory homogeneity in four coagulation tests. Non-reconstituted samples presented with satisfactory stability at 37°C for 2 hours and 4 hours and at room temperature for 1 day, while reconstituted samples presented with satisfactory stability when refrigerated at 4°C for 4 hours, when kept at room temperature for 4 hours, and when frozen at -80°C for 6 months.

A synthetic aperture radar (SAR) system can be seriously contaminated by radio frequency systems because of working in the same microwave frequency bands, which would degrade the SAR image quality and affect the accuracy of image interpretation. In this paper, a novel radio frequency interference (RFI) suppression approach including RFI identification, band-stop filtering and a removed spectrum iterative adaptive approach (RSIAA) is proposed. First, the smoothing process is added before RFI signal detection to improve the RFI detection capacity. Afterwards, the band-stop filtering with a broaden factor is proposed to mitigate the residual RFI, and it ensures the accuracy of the following removed spectrum recovery by the RSIAA. Finally, the removed spectrum components are estimated from available adjacent spectrum data by the RSIAA in turn to obtain the desired range spectra. Compared with the conventional range frequency filtering method for RFI suppression, the capacity of the weak RFI signal detection is improved, and the increased sidelobes due to the discontinuous spectra are well suppressed. Simulation experiments on both simulated SAR raw data, Gaofen-3 and Sentinel-1 SAR raw data validate the proposed RFI suppression approach.

The radar with arc antenna array has the advantages of all-orientation space scanning, simultaneous estimation of pitch-azimuth angle and good antenna pattern. However, due to the special geometry of the antenna, the snapshots from different range cells are not independently and identically distributed (IID) samples, resulting in performance degradation in space-time adaptive processing (STAP). In this paper, the model of airborne radar with arc antenna array is established. The improved arc array-based iterative adaptive approach (IAA) algorithm is studied. The IAA algorithm is utilized to estimate the space-time spectrum. The sparse constraint method is used to reduce the clutter ridge width and improve the ability of suppressing clutter and detecting targets. Simulation experiments verify the effectiveness of the IAA algorithm in arc array radar.

The purpose was to evaluate the correlation of the pre-treatment hematological parameters with metabolic parameters of primary tumor in baseline 18F-FDG PET/CT in patients with colorectal cancer (CRC) and estimate the prognostic value of both. We retrospectively investigated 231 patients with CRC who underwent baseline 18F-FDG PET/CT. Routine blood sampling was tested in the same term. PET parameters in term of hematological parameters and pathological characteristics of primary tumor were compared. Kaplan–Meier survival analysis was performed in the patients without distant metastasis. The differences of disease-free survival between groups were compared by log-rank tests. Neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) were significantly correlated with all the metabolic parameters including maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV) and tumor lesion glycolysis (TLG). The patients with NLR > 3 had higher MTV (24.82 ± 18.16 vs 19.06 ± 13.30, P = 0.039) and TLG (219.04 ± 186.94 vs 166.45 ± 146.39, P = 0.047) than those whose NLR ≤ 3. NLR in those patients with distant metastasis was significantly higher than those without distant metastasis (P = 0.018) while LMR in those patients with distant metastasis was significantly lower than those without distant metastasis (P = 0.032). Survival analysis showed that those patients with low MTV (P = 0.015), low NLR (P = 0.008) and high LMR (P = 0.027) revealed significant survival benefit. There was a significant association between the pre-treatment hematological parameters and metabolic parameters of baseline 18F-FDG PET/CT in the patients with CRC. It might be helpful in those patients with high NLR and low LMR to undergo 18F-FDG PET/CT to detect distant metastasis and predict prognosis.

A knowledge-aided direct data domain (D3) algorithm, which is applied to the space-time adaptive processing (STAP), is proposed. The conventional D3 algorithm only uses the test data to avoid heterogeneous training data. However, the prior knowledge of target is always not accurate, leading to performance degradation. The D3 algorithm based on sparse representation suffers target self-nulling and clutter suppression performance degradation. To overcome these disadvantages, a knowledge-aided D3 algorithm is proposed to improve the STAP performance. The prior knowledge about clutter distribution of forward-looking airborne radar is exploited to distinguish clutter components and targets. Furthermore, the clutter components can be eliminated from the sparse recovery coefficient vector. Hence, we can judge if the targets are present via the power of reminder element. Then, the clutter components are exploited to estimate the STAP filter weight, which can supply satisfactory clutter suppression performance. Experiments validate that the proposed algorithm separate the clutter components and targets directly without the prior knowledge of targets, and the target detection performance is improved significantly.

Space-Time Adaptive Processing (STAP) of airborne radar has significant performance degradation with few snapshots and dense interferences. Devoting to this problem, this paper proposes a knowledge-aided Pre-Whitening color loading sparse recovery robust STAP method (PW-SR-STAP). Firstly, the algorithm constructs the priori covariance matrix for the color loading matrix. And then, the snapshots are sparsely processed, the dense interference is removed according to the prior knowledge of clutter distribution. Hence, the clutter covariance matrix can be estimated accuracy. The advantage of this algorithm is that the number of snapshots is small, and the performance of target detection is improved. Simulation experiments verify that the effectiveness and robustness of the proposed algorithm are excellent.

Arc-array synthetic aperture radar (AA-SAR) has become a novel imaging scheme for full azimuth observation. However, the exiting arc-array monostatic SAR system is placed on a single platform and is easy to detect. Arc-array bistatic SAR (AA-BiSAR) with a stationary transmitter is proposed in this paper, which can obtain high data acquisition efficiency and reduce vulnerability of arc-array monostatic SAR. Furthermore, since the azimuth resolution with full azimuth observation is not related to the location of the stationary transmitter, the transmitter can be placed far away from the receiver. Compared with imaging algorithms for other modes, the key points of AA-BiSAR imaging algorithms are a square root in the bistatic slant range equation and an arc synthetic array in azimuth. According to the imaging geometry of AA-BiSAR, a novel imaging approach for AA-BiSAR based on keystone transform (KT) is proposed, and the KT implements range-cell migration correction (RCMC) in conditions of trigonometric function under square root in the range history and arc synthetic array in azimuth via reformatting the AA-BiSAR raw data. Besides presenting the proposed imaging approach, a complete resolution analysis of AA-BiSAR is given. Results of numerical simulation experiments on point targets validate the proposed imaging approach.

The Polarimetric target decomposition method based on scattering model is a hotspot, but there is a problem that decomposition results are inconsistent with actual scattering of ground objects. In order to solve the problem, a new polarimetric SAR data decomposition method based on generalized volume scattering model is proposed in this paper. Matrix rotation theory on basis of the dominant scatterer is used in the method, which removes cross-polarized scattering power generated by the coupling between orthogonal states of polarization. On this basis, a suitable volume scattering model is selected, which ultimately makes decomposition results are closer to scattering characteristics of ground objects and reduces the number of negative power pixels. Experiments show that the results of novel decomposition method reflect the scattering characteristics of real objects more accurately.

The detection of high-voltage power lines plays an important role in helicopter flight safety. Firstly, geometric model of high voltage power lines is established, and its Bragg scattering characteristics are introduced through theoretical analysis. Then, Radar Cross Section (RCS) of the high voltage line is simulated in millimeter wave band, and the Bragg scattering pattern is obtained, Bragg scattering characteristics of the high voltage line varying with frequency are analyzed. Finally, we compare full polarization scattering characteristics of the high voltage power line at 35 GHz with 94 GHz, and analyze the reflection characteristics of circular polarized waves by cylinders and high voltage lines.

Aiming at the problem of the number of residual points due to environmental noise in the interference phase diagram, it will cause some loss to the phase unwrapping and terrain deformation inversion precision. This paper proposes a phase-preserving filtering method based on contourlet transform. The method adopts the idea of multi-resolution and multi-direction, which leads to the improvement of the performance of the method. Firstly, the image is decomposed by using a directional filter; the second is to perform phase-preserving filtered on the decomposed image. Compared with the traditional methods, this method has a significant drop in the residual point, and the calculation amount is small, which is suitable for processing the measured data. In this paper, the effectiveness of the proposed algorithm is verified by InSAR data.

The radar with arc antenna array has the advantages of all-orientation space scanning, simultaneous estimation of pitch-azimuth angle and good antenna pattern. However, due to the special geometry of the antenna, the echoes from different range cells are not independently and identically distributed (IID) samples, resulting in performance degradation in space-time adaptive processing technology. In this paper, the model of airborne radar with arc antenna array is established, and the clutter distribution is analyzed. The conclusion is that the nonlinear variation of spatial angular frequency with array element number results in the non-uniform clutter distribution in different range cells. Therefore, the traditional space-time adaptive processing is not fit for the target detection of arc array radar. Hence, the arc array-based iterative adaptive approach (IAA) algorithm is studied. The IAA algorithm is utilized to estimate the space-time spectrum, which can distinguish clutter and targets. Simulation experiments verify the effectiveness of the IAA algorithm in arc array radar.

Space-time adaptive processing (STAP) for airborne radar may cause lattice mismatch during sparse recovery processing, which is the off-grid problem. The off-grid problem may lead to degradation of STAP performance. To cope with this problem, this paper proposes a knowledge-aided sparse recovery STAP algorithm with off-grid self-calibration (AO-SR-STAP). The snapshots are decomposed by sparse processing firstly. The off-grid of spare dictionary is calibrated and dense interferences are removed according to the knowledge of clutter distribution. A standard steering vector set is constructed by the prior knowledge of clutter distribution, which is used to calibrate the off-grid of sparse dictionary. The dense interferences in snapshots are removed with knowledge of clutter distribution. Hence, the clutter information of snapshots is estimated accurately and the target in cell under test can be detected completely. The advantage of this algorithm is that the off-grid of sparse dictionary can be calibrated, and dense interferences are filtered effectively. Simulation experiments verify the effectiveness and robustness of the proposed algorithm.

In a multichannel geosynchronous spaceborne–airborne bistatic synthetic aperture radar (GEO-SA-BiSAR) system, the airborne receiver can obtain high-resolution microwave images with good signal-to-noise ratios (SNRs) by passively receiving echoes from the desired area. Since the Doppler modulation and range history of a moving target are obviously different from a stationary target, a signal geometry model for moving targets in multichannel GEO-SA-BiSAR is established in this paper. According to simulation results, the along track velocity introduces target defocusing in azimuth, and the slant range velocity mainly causes multiple false targets. To resolve these problems, a modified multichannel reconstruction method in azimuth channel GEO-SA-BiSAR is proposed according to the azimuth multichannel impulse response of the imaged moving target. Before azimuth multichannel raw data combination, both spatial-variant range cell migration correction (RCMC) and azimuth nonlinear chirp scaling (ANLCS) should be performed to reduce the influence of the range offset and lower the Doppler bandwidth of the whole raw data, respectively. Afterward, a novel azimuth multichannel reconstruction algorithm is carried out via the modified reconstruction matrix based on the estimated target velocity. The target slant range velocity estimation is implemented by introducing the signal intensity ratio (SIR). Compared with the conventional method for the stationary target to handle the raw data of the moving target, the false targets could be obviously suppressed by using the proposed approach. Imaging results on both simulated point and distributed scene targets validate the proposed multichannel reconstruction approach.

The purpose was to evaluate the correlation of the pre-treatment hematological parameters with metabolic parameters of primary tumor in baselineWe retrospectively investigated 231 patients with CRC who underwent baselineNeutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) were significantly correlated with all the metabolic parameters including maximum standardized uptake value (SUVThere was a significant association between the pre-treatment hematological parameters and metabolic parameters of baseline

Human migration, influenced by social conflict and natural disasters as well as global climate change, has become recognized as a major "planetary force." It has also brought to the forefront, new specialties of integrative biology-such as high-altitude medicine-and the impact of hitherto understudied environmental factors on human pathophysiology in these new geographical settings. For people migrating to or living in high-altitude regions, environmental hypoxia is a primary challenge. Decreased partial pressure of oxygen in environmental air, caused by lower barometric pressure, puts living organisms in a hypoxic state. When there is a serious inability to adapt, death may ensue. Research efforts over the past few years have applied mass spectrometry-based proteomics analyses to uncover the mechanisms of hypoxia-related high-altitude pathophysiology. The differential proteomic profiles in plasma and tissues under high-altitude hypoxia conditions, as compared with sea level controls, and the multitudinous hypoxia-specific proteins identified elucidate mechanisms underlying high-altitude hypoxia acclimatization and diseases, and provide a foundation for development of new therapeutic, prophylactic, and diagnostic approaches. In this expert review and innovation analysis, we highlight the current proteomics findings on high-altitude hypoxia, and suggest paths forward toward effective interventions to address this key challenge in high-altitude medicine.

A hypoxic microenvironment effects various signaling pathways in the human body, including those that are critical for normal physiology and those that support tumorigenesis or cancer progression. A hypoxic tumor microenvironment, in particular, modulates cell migration, invasion and resistance to radiotherapy and chemotherapy. Development of the mass spectrometry (MS) technique has allowed for expansion of proteomic study to a wide variety of fields, with the study of tumor hypoxia being among the latest to enjoy its benefits. In such studies, changes in the proteome of tumor tissue or cells induced by the hypoxic conditions are analyzed. A multitude of hypoxic regulatory proteins have already been identified, increasing our understanding of the mechanisms underlying tumor occurrence and development and representing candidate reference markers for tumor diagnosis and therapy. The present review provides the first summary of the collective studies on tumor microenvironment hypoxia that have been completed using MS-based proteomic techniques, providing a systematic discussion of the benefits and current challenges of the various applications.

Using two (238)U samples placed in a gridded ionization chamber and a parallel-plate fission chamber, fluence of monoenergetic fast neutrons was determined. Four runs of measurements were performed. Analysis showed that although the neutron fluences for the two (238)U samples differ by 20-33 times in the present work, the fluences at the position of the sample in the gridded ionization chamber determined by the two ways are in agreement within experimental uncertainties.

A series of aromatic polyimides (PI-IIa–d) containing lateral phenylphosphine oxide (PPO) and trifluoromethyl (–CF3) moiety were prepared from an aromatic diamine, 2,5-bis[(4-amino-2-trifluoromethylphenoxy)phenyl]diphenyl-phosphine oxide (BATFDPO) and various aromatic dianhydrides via a two-step chemical imidization procedure. In parallel, for comparison, another series of polyimides (PI-Ia–d) without trifluoromethyl were synthesized from a diamine, 2,5-bis[(4-aminophenoxy)-phenyl]diphenylphosphine oxide (BADPO) and the same dianhydrides. It was found that both of the two series of polyimides (PIs) were soluble in polar aprotic solvents, such as N-methyl-2-pyrrolidinone (NMP) and the solubility of PI-IIa–d was highly enhanced by the introduction of the bulky –CF3 group. Flexible and tough PI films with tensile strengths higher than 70 MPa were cast from the PI solution. The introduction of –CF3 moiety slightly sacrificed the thermal stability and mechanical properties of the PI films. For example, PI-IIa–d showed 5% weight loss at 472–476 °C, which was about 50 °C lower than those of their PI-Ia–d analogues. However, –CF3 group apparently improved the optical transparency and decreased the refractive indices of the PI films. PI-IId derived from BATFDPO and 4,4’-hexafluoroisopropylidenediphthalic anhydride (6FDA) exhibited the highest optical transparency with the transmittance of 90% at 400 nm and the refractive index as low as 1.5511 at 1310 nm.

Anthrax, caused by the pathogenic bacterium Bacillus anthracis, is a zoonosis that causes serious disease and is of significant concern as a biological warfare agent. Validating annotated genes and reannotating misannotated genes are important to understand its biology and mechanisms of pathogenicity. Proteomics studies are, to date, the best method for verifying and improving current annotations. To this end, the proteome of B. anthracis A16R was analyzed via one-dimensional gel electrophoresis followed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). In total, we identified 3,712 proteins, including many regulatory and key functional proteins at relatively low abundance, representing the most complete proteome of B. anthracis to date. Interestingly, eight sequencing errors were detected by proteogenomic analysis and corrected by resequencing. More importantly, three unannotated peptide fragments were identified in this study and validated by synthetic peptide mass spectrum mapping and green fluorescent protein fusion experiments. These data not only give a more comprehensive understanding of B. anthracis A16R but also demonstrate the power of proteomics to improve genome annotations and determine true translational elements.

Plasmid-cured derivative strains of Bacillus anthracis are frequently used in laboratory studies. Plasmid incompatibility, which does not increase the risk of chromosomal mutation, is a useful method for plasmid curing. However, in bacteria containing multiple plasmids, it often requires the sequential introduction of multiple, specific incompatibility plasmids. This lengthy process renders the traditional plasmid incompatibility method inefficient and mutation-prone. In this study, we successfully cured plasmids pXO1 and pXO2 from B. anthracis A16 simultaneously using only one recombinant incompatible plasmid, pKORT, to obtain a plasmid-free strain, designated A16DD. This method may also be useful for the simultaneous, one-step curing of multiple plasmids from other bacteria, including Bacillus thuringiensis and Yersinia pestis.

To investigate the polymorphism of clustered regularly interspaced short palindromic repeats (CRISPR) in Bacillu santhracis and the application to molecular typing based on the polymorphism of CRISPR in B. anthracis.We downloaded the whole genome sequence of 6 B. anthracis strains and extracted the CRISPR sites. We designed the primers of CRISPR sites and amplified the CRISPR fragments in 193 B. anthracis strains by PCR and sequenced these fragments. In order to reveal the polymorphism of CRISPR in B. anthracis, wealigned all the extracted sequences and sequenced results by local blasting. At the same time, we also analyzed the CRISPR sites in B. cereus and B. thuringiensis.We did not find any polymorphism of CRISPR in B. anthracis.The molecular typing approach based on CRISPR polymorphism is not suitable for B. anthracis, but it is possible for us to distinguish B. anthracis from B. cereus and B. thuringiensis.

An attenuated Bacillus anthracis vaccine strain for human use, A16R, was obtained in China after ultraviolet radiation treatment and continuous subculture of the wild-type strain A16. A16R can synthesize the exotoxin, but without a capsule. We sequenced and annotated the A16R genome to encourage the use of this strain. The genome sequencing of the wild-type strain A16 is underway and the genomic comparison between the two strains will help to illustrate the attenuating mechanism of the A16R vaccine strain.