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Pilot‐ignited ammonia‐fueled engines have drawn more and more attention for low carbon emissions compared to traditional diesel engines. The ignition processes of NH3/NC7H16 mixtures under compression ignition engine‐like conditions are numerically investigated. By comparing the ignition delay times (IDTs) calculated by six ammonia mechanisms with experimental data, the Glarborg mechanism is selected. Then, the Glarborg mechanism and the Zhang detailed n‐heptane mechanism are merged into a new mechanism, which is adopted in the present study. Results show that the negative temperature coefficient behavior of the IDTs is only observed as the ammonia mass fraction is 70%. Only temperature has a significant effect on IDTs at all research conditions, and the effect of ammonia mass fraction is significant when the temperature is lower than 1000 K. However, the effects of equivalence ratio and pressure are small, especially at high temperatures, high equivalence ratios, and high pressures. Interestingly, the IDTs are categorized into three regions by temperature and ammonia mass fraction. The sensitivity analysis indicates that the sensitivity coefficients of most reactions associated with ammonia decrease with a decrease in ammonia mass fraction, whereas only R4210 is sensitive to ammonia mass fraction for n‐heptane‐related reactions. Rates of production and consumption (ROP) analyses indicate that the ammonia mass fraction mainly affects the ROPs of NC7H16, NH3, and NNH at low and medium temperatures, whereas the ammonia mass fraction affects the ROP of H2NO before the temperature of 2000 K. The ROPs of NC7H16, NH3, and NNH significantly increase with increasing temperature, whereas the ROP of H2NO slightly increases with increasing temperature. The increase of temperature in the early and middle stages is mainly contributed by the oxidation of n‐heptane, while the increase of temperature in the middle and late stages is mainly contributed by the oxidation of ammonia. [ABSTRACT FROM AUTHOR]

This study attempts to determine whether there is a spatial correlation between electricity generation and economic scale promoting coordinated development in Africa. We explore the spatial similarity and gray correlation degree between electricity generation and economic scale in Africa since the 21st century by adopting barycenter coupling and Gray Correlation Analysis method. We argue that there is a strong correlation between electricity generation and economic scale. Our findings indicate a significant spatial difference in electricity generation, mainly concentrated in Northern and Southern Africa. Furthermore, spatial pattern remains largely consistent over time, mirroring trends observed at the economic scale. Electricity generation and economic scale were concentrated in six countries- South Africa, Egypt, Algeria, Nigeria, Morocco, and Libya- and did not change significantly over time. A correlation analysis between electricity generation and the economic scale further confirmed this, with a linear coefficient of 0.907. Both the gravity centers of economic scale and electricity generation in Africa move farther in the north-south direction than in the East-West direction, with the former showing a Southwest-Northeast-Southwest track feature and the latter a Northeast-Southwest track feature. The spatial distribution of the gravity centers of electricity generation and the gravity centers of the economic scale in Africa are highly consistent; electricity generation highly correlates with the economic scale, consistent with the research conclusion obtained by the Gray Correlation Analysis method. This study suggests the coordinated development of electricity generation and economic scales in various African countries. [ABSTRACT FROM AUTHOR]

The calibration of channel imbalances is currently the main concern in polarimetric calibration (POLCAL) since the crosstalk of recent polarimetric synthetic aperture radar (Pol-SAR) systems is lower than −20 dB. The existing channel imbalance calibration method without corner reflectors utilizes both volume-dominated and Bragg-like targets. However, there are two limitations to using volume-dominated targets. One is that the inaccurate selection of volume-dominated areas in the uncalibrated Pol-SAR images has a negative influence on the estimation of cross-polarization (x-pol) channel imbalance, which subsequently impacts the estimation of copolarization (copol) channel imbalance. The other is that there are minimal volume-dominated areas in some special applications of Pol-SAR, such as planetary exploration. Thus, only selecting Bragg-like targets to estimate the values of both transmitting and receiving channel imbalances, which is proposed in this paper, can avoid the uncertainty brought about by selecting other distributed targets in an uncalibrated imaginary. In addition, the reciprocity assumption and characteristics corresponding to H/ α ¯  decomposition are introduced to eliminate the phase ambiguity for the first time. Compared with previous methods, our method had an obvious advantage in terms of universality, since Bragg-like targets are common in the most illuminating areas. The novel method was applied to both the simulated data from the L-band Advanced Land Observing Satellite (ALOS) and C-band GaoFen-3 (GF-3), and to real data with corner reflectors on site. The results from the simulated data showed that the errors of the amplitude and phase estimation were less than 0.5 dB and 5.0° in most topographical features. Meanwhile, the  V V / H H  terms from all trihedral corner reflectors were less than 0.3 dB for amplitude, and 5.5° for phase after calibration by using the estimated channel imbalances. [ABSTRACT FROM AUTHOR]

Purpose. Cancer development and immune escape involve DNA methylation, copy number variation, and other molecular events. However, there are remarkably few studies integrating multiomics genetic profiles into endometrial cancer (EC). This study aimed to develop a multiomics signature for the prognosis and immunotherapy response of endometrial carcinoma. Methods. The gene expression, somatic mutation, copy number alteration, and DNA methylation data of EC were analyzed from the UCSC Xena database. Then, a multiomics signature was constructed by a machine learning model, with the ROC curve comparing its prognostic power with traditional clinical features. Two computational strategies were utilized to estimate the signature's performance in predicting immunotherapy response in EC. Further validation focused on the most frequently mutant molecule, ARID1A, in the signature. The association of ARID1A with survival, MSI (Microsatellite-instability), immune checkpoints, TIL (tumor-infiltrating lymphocyte), and downstream immune pathways was explored. Results. The signature consisted of 22 multiomics molecules, showing excellent prognostic performance in predicting the overall survival of patients with EC (AUC = 0.788). After stratifying patients into a high and low-risk group according to the signature's median value, low-risk patients displayed a greater possibility of respond to immunotherapy. Further validation on ARID1A suggested it could induce immune checkpoints upregulation, promote interferon response pathway, and interact with Treg (regulatory T cell) to facilitate immune activation in EC. Conclusion. A novel multiomics prognostic signature of EC was identified and validated in this study, which could guide clinical management of EC and benefit personalized immunotherapy. [ABSTRACT FROM AUTHOR]

Soil salinization is a global problem, which seriously damages the ecological environment and considerably reduces agricultural productivity, especially in arid regions. Synthetic aperture radar (SAR) has been widely used in remote sensing due to its weather and sunlight independence. Polarimetric SAR has great potential for large-scale mapping and monitoring salt-affected soils. In this study, we investigate the characteristics of saline soil in extremely arid regions using dual-band quadrature-polarimetric (quad-pol) SAR images acquired by GF-3 (C-band) and ALOS-2 (L-band). Firstly, the effectiveness of the modified dielectric mixing model and integral equation model (IEM) in describing saline soil is evaluated. Secondly, the potential relationships between polarimetric parameters and salinity are discussed in both the C- and L-band, respectively, such as co-polarization ratio, scattering entropy H, and scattering angle α. Finally, a linear regression model for monitoring salt content is established. The main contributions of this article are as follows: (1) Simulation results suggest that the radar backscattering coefficient is a weak function of salinity at low water content, but our experimental data show that soil salinity significantly contributes to the radar backscattering coefficient, which indicates the modified dielectric mixing model and IEM model is not applicable in extremely arid areas. (2) A negative correlation between the co-polarization ratio and salinity is observed, and the correlation coefficients are 0.64 (C-band) and 0.71 (L-band). Besides, scattering entropy and scattering angle exhibit a positive correlation with salinity in the C-band with correlation coefficients 0.686 and 0.669, respectively, whereas a negative correlation is found in the L-band with correlation coefficients 0.682 and 0.680, respectively. This can be attributed to the different penetration depths and sensitivity to the surface roughness of the electromagnetic waves at two frequencies. (3) A regression model for salinity estimating based on radar backscattering coefficient, co-polarization ratio, and scattering entropy is established, with a determination coefficient ( R 2 ) of 0.79 and a root mean square error (RMSE) of 6.56%, allowing us to determine soil salinity from quad-pol SAR images without using backscattering models. Therefore, our results can be a reference for future soil salinity monitoring and inversion. [ABSTRACT FROM AUTHOR]

Polarimetric synthetic aperture radar (SAR) has been extensively used in various remote sensing applications. In this article, a unified framework is designed to compare the classification performance of different polarimetric systems, which include quad-polarimetric (QP), compact-polarimetric (CP), and dual-polarimetric (DP). To avoid problems, such as the lack of uniform standards in feature extraction, the classification algorithm is directly based on the statistical characteristics of the coherency/covariance matrix and is implemented by extending the Wishart mixture model (WMM). The GF-3 data set in San Francisco and the AIRSAR agricultural data set in Flevoland are used in the experiment, and the following conclusions are generated. QP can achieve the highest classification accuracy in all classification tasks. When distinguishing three typical classes (water, urban, and vegetation) with very different scattering characteristics, the performance of different polarimetric systems is similar, and QP has only a slight advantage. For classification tasks of different classes with similar scattering characteristics, CP performs better in agricultural scenes, and the overall accuracy (OA) is only reduced by 3%–4% compared with QP. DP performs better in urban scenes, and OA is only reduced by 1%–3% compared with QP. These conclusions can provide guidance for future payloads’ design and the choice of polarimetric operation mode for existing multi-polarimetric SAR systems to achieve the purpose of giving full play to the advantages of different polarimetric systems. [ABSTRACT FROM AUTHOR]

As polarimetric antennas can be isolated through excellent electronic frameworks in circular quad-polarization (CQP) synthetic aperture radar (SAR) systems, cross-polarization (x-pol) and co-polarization (co-pol) channel imbalances are more challenging and essential to calibrate than crosstalk in polarimetric calibration (PolCAL). In uncalibrated CQP SAR images without corner reflectors (CRs), the reciprocity and reflection symmetry assumptions of the distributed targets are commonly used to estimate the x-pol and co-pol channel imbalances, respectively. To suppress the influence of additive noise on determining channel imbalances through distributed targets, high signal-to-noise ratio (SNR) distributed targets should be obtained from the x-pol and co-pol channels of the CQP SAR images: namely, surface-dominated and volume-dominated targets. However, some reflection symmetry assumptions used in the existing calibration literature have poor applicability with volume-dominated targets, resulting in unsatisfactory estimation results for the co-pol channel imbalance phase. In this paper, we assess the priority of the reflection symmetry properties of volume-dominated targets used to calibrate the co-pol channel imbalance phase in CQP SAR data synthesized from linear quad-polarization data of ALOS, GF-3, and RADARSAT-2. In the theoretical part, high-priority reflection symmetry (termed semireflection symmetry) assumptions are confirmed as the most suitable for estimating the co-pol channel imbalance phase, and were selected to develop an algorithm for estimating the co-pol channel imbalance phase. Furthermore, based on the novel method for estimating the co-pol channel imbalance phase, a channel imbalance calibration scheme is proposed for CQP SAR systems with reciprocal crosstalk, including extracting surface-dominated and volume-dominated targets, and estimating and filtering channel imbalances. We demonstrate the effectiveness of our proposed scheme with CRs in simulated CQP SAR images. The experimental results show that the calibration scheme is an effective workflow for estimating channel imbalances in CQP SAR systems with reciprocal crosstalk. [ABSTRACT FROM AUTHOR]

The Wishart mixture model is an effective tool for characterizing the statistical distribution of polarimetric synthetic aperture radar (PolSAR) data. However, due to the difficulty in determining the equivalent number of looks, the Wishart mixture model has some problems in terms of practicality. In addition, the flexibility of the Wishart mixture model needs to be improved for complicated scenes. To improve the practicality and flexibility, a new mixture model named the relaxed Wishart mixture model (RWMM) is proposed. In RWMM, the equivalent number of looks is no longer considered a constant for the whole PolSAR image but a variable that varies between different clusters. Next, an innovative algorithm named RWMM-Markov random field (RWMM-MRFt) for supervised classification is proposed. A new selection criterion for adaptive neighborhood systems is proposed in the algorithm to improve the classification performance. The new criterion makes effective use of PolSAR scattering information to select the most suitable neighborhood for each center pixel in PolSAR images. Three datasets, including one simulated image and two real PolSAR images, are utilized in the experiment. The maximum likelihood classification results demonstrate the flexibility of the proposed RWMM for modeling PolSAR data. The proposed selection criterion shows superior performance than the span-based selection criterion. Among the mixture model-based MRF classification algorithms, the proposed RWMM-MRFt algorithm has the highest classification accuracy, and the corresponding classification maps have better anti-noise performance. [ABSTRACT FROM AUTHOR]

While both protein-polysaccharide complexes and continuous phase gelation showed great potential for stabilizing high internal phase Pickering emulsions (HIPPEs), it is not known which strategies are more effective and adaptive. In this work, HIPPEs gel was prepared by Ca2+-induced continuous phase gelation of ovalbumin (OVA)-low methoxyl pectin (LMP) electrostatic complexes particles (OLECP)-stabilized HIPPEs. The microstructure, rheological properties, stability, and application of HIPPEs and HIPPEs gel were systematically investigated and compared at different LMP concentrations. The results showed that, compared to HIPPEs, continuous phase gelation effectively improved the viscoelasticity, water binding capacity, and hardness of HIPPEs gel due to its robust and developed interface architecture. CLSM and cryo-SEM observations revealed that OLECP interconnected with each other in the continuous phase to form an advanced network architecture in HIPPEs. Whereas, a firm gel network structure and a thick interfacial layer were found in HIPPEs gel. More importantly, with increasing pectin concentration, the cross-linking phenomenon of OLECP mainly at the interface, transformed into the gelation behavior of excess pectin molecules dominating in the continuous phase. LMP contributed to the formation of a finer 3D gel network structure and a firmer interfacial layer, providing a smaller oil droplet size and superior stability for HIPPEs gel. The photochemical stability of curcumin was increased from 16.1 ± 1.5 % to 93.7 ± 2.2 % after encapsulation in HIPPEs gel. In vitro digestion results testified that HIPPEs gel (10:15, w/w) can promote fat hydrolysis (from 32.35 ± 3.06 % to 45.52 ± 2.75 %) and enhance the bioaccessibility of curcumin (from 20.1 ± 1.5 % to 32.8 ± 2.6 %) compared to bulk oil. Besides, compared with HIPPEs, HIPPEs gel showed poor printability because of improper printing adaptability and liquidity. In a nutshell, our work provides valuable information for developing novel HIPPEs gels for various food applications. [Display omitted] • Calcium ions induced interfacial gelation of OVA-LMP electrostatic complex particles. • Interfacial gelation effectively improved the stability of HIPPEs. • The novel HIPPEs gel had a robust interface architecture via developed gel networks. • HIPPEs gel exhibited extraordinary encapsulation capability and poor printability. [ABSTRACT FROM AUTHOR]

Polarimetric synthetic aperture radar (PolSAR) data provide an alternative way for topography retrieval, especially when limited PolSAR data are available. This article proposes a novel topography retrieval algorithm based on the Lambertian backscatter model that further improves the vertical precision of digital elevation model (DEM) generation and requires only one flight. The key idea of the proposed algorithm is to avoid data fluctuations caused by the ratio of the azimuth slope angle to the polarimetric orientation angle (POA). The previous research has confirmed the feasibility of generating a DEM based on single-pass PolSAR data, but its effect on the quality of reference DEM has not been well-explained. To analyze this effect, a large number of experiments on DEM with different resolutions are conducted. In addition, an in-depth analysis of non-linear and terrain-dependent errors is performed. The L-band PolSAR data of NASA/JPL TOPSAR and ALOS-2 PALSAR-2 and interferometric SAR (InSAR) DEM data are used to verify the proposed algorithm. The experimental results show that PolSAR data can be used as an additional reliable information source for DEM fusion under certain conditions to improve the quality of public DEM. [ABSTRACT FROM AUTHOR]

Androgen receptor (AR) variants are associated with resistance to anti androgen therapy both in human prostate cancer cell lines and clinical samples. These observations support the hypothesis that AR isoform accumulation is a consequence of selective therapeutic pressure on the full length AR. The Pten deficient prostate cancer model proceeds with well-defined kinetics including progression to castration resistant prostate cancer (CRPC). While surgical castration and enzalutamide treatments yield an initial therapeutic response, Pten-/-epithelia continue to proliferate yielding locally invasive primary tumor pathology. That most epithelium remains AR positive, but ligand independent, suggests the presence of oncogenic AR variants. To address this hypothesis, we have used a panel of recently described Pten-/- tumor cell lines derived from both from hormone intact (E4, E8) and castrated Pten mutants (cE1, cE2) followed by RACE PCR to identify and characterize three novel truncated, amino terminus containing AR variants (mAR-Va, b, c). Variants appear not only conserved throughout progression but are correlated with nearly complete loss of full length AR (AR-FL) at castrate androgen levels. The overexpression of variants leads to enhanced transcriptional activity of AR while knock down studies show reduced transcriptional output. Collectively, the identification of truncated AR variants in the conditional PTEN deletion model supports a role for maintaining the CRPC phenotype and provides further therapeutic applications of this preclinical model. [ABSTRACT FROM AUTHOR]

Calibration using corner reflectors is an effective way to estimate the distortion parameters of hybrid compact polarimetric (HCP) synthetic aperture radar (SAR) systems. However, the existing literature lacks a discussion on the inconsistency of the amplitude and phase coefficients between measured scattering vectors of different corner reflectors. In response to this problem, this paper first proves that this inconsistency will seriously deteriorate the estimation accuracy of polarimetric distortion parameters. Based on the optimization algorithm, two calibration schemes for simultaneously estimating the traditional distortion parameters and the amplitude/phase coefficients are proposed while ignoring crosstalk (ICT) and considering crosstalk (CCT). In the process of distortion parameter estimation, the idea of "optimizing while compensating" is adopted to eliminate the problem of uneven echo intensity. Simulation results show that both schemes can eliminate the influence of the inconsistency of amplitude and phase coefficients, and estimate distortion parameters accurately. When the received crosstalk level is lower than −30 dB, the ICT scheme can accurately estimate polarimetric distortion parameters. The CCT scheme has a wider application range of crosstalk and can work well when the crosstalk level is lower than −20 dB, but it also has a higher requirement for the signal-to-clutter ratio (SCR). When SCR is greater than 35 dB, the CCT scheme yields higher estimation accuracy than the ICT scheme. In addition, the effectiveness of the calibration schemes is verified based on the L-band measured data acquired by the Aerospace Information Research Institute, Chinese Academy of Sciences. [ABSTRACT FROM AUTHOR]

Hybrid-polarimetric architecture may become a new option for spaceborne quadrature-polarimetric (quad-pol) synthetic aperture radar (SAR) mainly due to the range ambiguity improvement without loss of polarization information. To inherit the analytical methods developed for the conventional quad-pol SAR data, it is necessary to transform the hybrid quad-pol SAR data into a linear polarimetric basis. However, this operation will result in deterioration of azimuth ambiguity performance. The theoretical analysis on range and azimuth ambiguities in quad-pol SAR has been relatively complete, which is also summarized in this article. Yet, there is no real data to verify the equivalence of polarization information and to compare the ambiguity levels. Based on P-band airborne experiment, real hybrid and conventional quad-pol SAR data are used for comparative verification. In addition, considering that polarimetric target decomposition is often used in the practical applications, we suggest a new perspective from target decomposition for the ambiguities in quad-pol SAR. Identical polarimetric processing results for two sets of comparative data verify that hybrid quad-pol SAR data are indistinguishable from conventional quad-pol SAR data. The demonstrated intensity images and decomposed RGB images with azimuth ambiguities, acquired by the two quad-pol modes, completely conform to the theory. [ABSTRACT FROM AUTHOR]

Elérh [ABSTRACT FROM AUTHOR]