Search

Background: Leaf morphology plays a crucial role in photosynthetic efficiency and yield potential in crops. Cigar tobacco plants, which are derived from common tobacco (Nicotiana tabacum L.), possess special leaf characteristics including thin and delicate leaves with few visible veins, making it a good system for studying the genetic basis of leaf morphological characters. Results: In this study, GWAS and QTL mapping were simultaneously performed using a natural population containing 185 accessions collected worldwide and an F2 population consisting of 240 individuals, respectively. A total of 26 QTLs related to leaf morphological traits were mapped in the F2 population at three different developmental stages, and some QTL intervals were repeatedly detected for different traits and at different developmental stages. Among the 206 significant SNPs identified in the natural population using GWAS, several associated with the leaf thickness phenotype were co-mapped via QTL mapping. By analyzing linkage disequilibrium and transcriptome data from different tissues combined with gene functional annotations, 7 candidate genes from the co-mapped region were identified as the potential causative genes associated with leaf thickness. Conclusions: These results presented a valuable cigar tobacco resource showing the genetic diversity regarding its leaf morphological traits at different developmental stages. It also provides valuable information for novel genes and molecular markers that will be useful for further functional verification and for molecular breeding of leaf morphological traits in crops in the future. [ABSTRACT FROM AUTHOR]

At present, a variety of global remote sensing surface downwelling longwave radiation (SDL) products are used for atmospheric science research; however, there are few studies on the quantitative evaluation of differences among different SDL products. In order to evaluate the differences among different SDL products quantitatively, we have selected three commonly used SDL products—Clouds and the Earth's Radiant Energy System-Synoptic Radiative Fluxes and Clouds (CERES-SYN), the European Centre for Medium Range Weather Forecasts-Surface Radiation Budget (ECMWF-SRB) and the Global Energy and Water Exchanges Project-Surface Radiation Budget (GEWEX-SRB)—to comprehensively study in this paper. The results show that there are significant differences among the three SDL products in some areas, such as in the Arctic, the Antarctic, the Sahara, the Tibet Plateau, and Greenland. The maximum absolute root mean square error (RMSEab) in these areas is greater than 20 Wm−2, the maximum relative root mean square error (RMSEre) is greater than 20%, the maximum and minimum absolute mean bias error (MBEab) are about 20 Wm−2 and −20 Wm−2, respectively, and the maximum and minimum relative mean bias error (MBEre) are about 10% and −10%, respectively. Among the three SDL products, the difference between the ECMWF-SRB and GEWEX-SRB is the most significant. In addition, this paper also analyzed the differences among different SDL products based on three aspects. Firstly, the differences among the three SDL products show that there is significant seasonality, and the differences among different months may vary greatly. However, the differences are not sensitive to years. Secondly, there are some differences in cloud-forcing radiative fluxes (CFRFs) of different SDL products, which is also an important factor affecting the difference between different SDL products. Finally, in the process of converting high temporal resolution SDL products into monthly SDL products, data processing also affects the difference between different SDL products. [ABSTRACT FROM AUTHOR]

Clouds are the major source of clutter in optical remote sensing (RS) images. Approximately 60% of the Earth's surface is covered by clouds, with the equatorial and Tibetan Plateau regions being the most affected. Although the implementation of techniques for cloud removal can significantly improve the efficiency of remote sensing imagery, its use is severely restricted due to the poor timeliness of time-series cloud removal techniques and the distortion-prone nature of single-frame cloud removal techniques. To thoroughly remove thin clouds from remote sensing imagery, we propose the Saliency Cloud Matting Convolutional Neural Network (SCM-CNN) from an image fusion perspective. This network can automatically balance multiple loss functions, extract the cloud opacity and cloud top reflectance intensity from cloudy remote sensing images, and recover ground surface information under thin cloud cover through inverse operations. The SCM-CNN was trained on simulated samples and validated on both simulated samples and Sentinel-2 images, achieving average peak signal-to-noise ratios (PSNRs) of 30.04 and 25.32, respectively. Comparative studies demonstrate that the SCM-CNN model is more effective in performing cloud removal on individual remote sensing images, is robust, and can recover ground surface information under thin cloud cover without compromising the original image. The method proposed in this article can be widely promoted in regions with year-round cloud cover, providing data support for geological hazard, vegetation, and frozen area studies, among others. [ABSTRACT FROM AUTHOR]

The Greenland Ice Sheet (GrIS) is the largest ice body in the Northern Hemisphere. Quantifying the spatiotemporal characteristics of its mass change is crucial for understanding global climate change. Many studies have been focused on the long-term ice mass change and acceleration, but a more detailed analysis of multitemporal signals, including annual, interannual and transient variations, is still imperative to study the periodic ice mass change. Here, we comprehensively characterize the multitemporal mass changes of the entire GrIS and subregions using a variational mode decomposition method, applied to Gravity Recovery and Climate Experiment satellite data, surface mass balance model output, climate parameters and GPS observations. We found that both the interannual and transient mass variations of the southern subregions have larger amplitudes associated with pronounced precipitations, indicating that the southern mass change patterns are more vulnerable to short-term climate variability. We also found that the reported rapid mass loss in 2010, 2012, 2016 and 2019 should be attributed to the interannual signals that result from low precipitations, significant runoff and evapotranspiration. The largest interannual mass variation was discovered in 2019 (−235 Gt), but due to the combined effect of interannual loss (−147 Gt) and transient attenuation (−380 Gt), the greatest mass loss (−527 Gt) was observed at the end of 2012. Our study emphasizes the importance of multitemporal signals in characterizing the spatiotemporal GrIS mass change and exploring the coupling effect between ice mass change and climate conditions. [ABSTRACT FROM AUTHOR]

The use of the conventional interferometric synthetic aperture radar (InSAR) to generate digital elevation models (DEMs) always encounters phase unwrapping (PU) errors in areas with a sizeable topographic gradient. Range split-spectrum interferometry (RSSI) can overcome this issue; however, it loses the spatial resolution of the SAR image. We propose the use of the RSSI-assisted In-SAR-derived DEM (RID) method to address this challenge. The proposed approach first applies the RSSI method to generate a prior DEM, used for simulating terrain phases. Then, the simulated terrain phases are subtracted from the wrapped InSAR phases to obtain wrapped residual phases. Finally, the residual phases are unwrapped by the minimum cost flow (MCF) method, and the unwrapped residual phases are added to the simulated phases. Both the simulated and TerraSAR-X data sets are used to verify the proposed method. Compared with the InSAR and RSSI methods, the proposed approach can effectively decrease the PU errors of large gradients, ensure data resolution, and guarantee the DEM's accuracy. The root mean square error between the topographic phase simulated from the real DEM and the topographic phase generated from the proposed method is 2.22 rad, which is significantly lower than 6.60 rad for InSAR, and the improvement rate is about 66.36%. [ABSTRACT FROM AUTHOR]

Mapping the outlines of glaciers has primarily relied on the interpretation of satellite optical images. However, the accurate delineation of glaciers in complex terrain mountain regions remains challenging, mainly because the supraglacial debris-covered ablation zones and snow-covered accumulation zones often exhibit the same spectral properties as their adjacent grounds in optical images. This study presents a novel approach by exploring both the satellite synthetic aperture radar (SAR) amplitude and interferometric coherence to map mountain glaciers. This method explores the deviation of the glacier surface signal in the SAR time series to distinguish glacier ice from the surrounding stable ground. To this end, we explored the classifying capabilities of two indices from a set of SAR images, SAR interferometric coherence and amplitude deviation index (ADI), to determine glacier boundary. We found that the two indices complement each other for mapping glaciers. A ratio map based on ADI and SAR coherence (ACR) was then derived, from which the glacier outline was automatically tracked using a specified threshold, followed by manual modification. We validated this approach on two typical valley glaciers, the debris-covered Hailuogou Glacier and debris-free Mozigou Glacier, in Mount Gongga in the southeastern Tibetan Plateau. The results show that the proposed ACR criteria can significantly enhance the contrast between glaciers and their surroundings. By comparing our results with manually delineated glacier outlines from high-resolution cloud-free satellite optical imagery, we found that the misclassification rate and difference rate for our results were 2.6% and 4.2%, respectively. The approach presented in this study can be easily adapted to map the outlines of mountain glaciers worldwide efficiently and is useful for inferring glacier boundary changes in a climate warming context. [ABSTRACT FROM AUTHOR]

Track irregularities are perhaps the main excitations of vehicle–track systems and cause dynamic wheel–rail responses, but track irregularities and vehicle responses do not always correspond to each other. In this study, the interrelations between track irregularities and vehicle responses in a multi-scale framework were investigated using measured data. Firstly, the track irregularity and vehicle response data were separated into modes on different time scales using multivariate empirical mode decomposition, and the energy distribution of each wavelength component was determined. Then, the local correlations between irregularity–response mode pairs were examined via time-dependent intrinsic correlation (TDIC) analysis. The irregularity–response interrelation was not always unique, but rather varied in both time scale and time domain, and positive–negative correlation reversals frequently occurred, causing a low overall correlation and coherence. TDIC analysis can elucidate the wavelengths and positions of track irregularities that affect vehicle responses. [ABSTRACT FROM AUTHOR]

Cephaleuros species are well-known as plant pathogens that cause red rust or algae spot diseases in many economically cultivated plants that grow in shady and humid environments. Despite their prevalence, the adaptive evolution of these pathogens remains poorly understood. We sequenced and characterized three Cephaleuros (Cephaleuros lagerheimii, Cephaleuros diffusus, and Cephaleuros virescens) chloroplast genomes, and compared them with seven previously reported chloroplast genomes. The chloroplast sequences of C. lagerheimii, C. diffusus, and C. virescens were 480,613 bp, 383,846 bp, and 472,444 bp in length, respectively. These chloroplast genomes encoded 94 genes, including 27 tRNA genes, 3 rRNA genes, and 64 protein-coding genes. Comparative analysis uncovered that the variation in genome size was principally due to the length of intergenic spacer sequences, followed by introns. Furthermore, several highly variable regions (trnY-GTA, trnL-TAG, petA, psbT, trnD-GTC, trnL-TAA, ccsA, petG, psaA, psaB, rps11, rps2, and rps14) were identified. Codon bias analysis revealed that the codon usage pattern of Cephaleuros is predominantly shaped by natural selection. Additionally, six chloroplast protein-coding genes (atpF, chlN, psaA, psaB, psbA, and rbcL) were determined to be under positive selection, suggesting they may play a vital roles in the adaptation of Cephaleuros to low-light intensity habitats. [ABSTRACT FROM AUTHOR]

The description and evaluation of track geometry irregularities are commonly performed in the distance domain or the frequency domain, and therefore one cannot simultaneously obtain precise measurements of actual frequencies and the distance locations where they appear. This paper proposes the time–frequency energy density (TFED) method to analyse the characteristics of track irregularities in the joint spatial distance–frequency plane. The proposed method describes the energy density distribution of track irregularities in the spatial distance–frequency domain based on the adaptive decomposition characteristics of the multivariate empirical mode decomposition and the time–frequency aggregation on the signal energy of the Hilbert spectrum. The mathematical relationships between the TFED and the standard deviation, as well as the power spectral density, are deduced and validated in the field data of track irregularities. The TFED method was applied to the spatial distance–frequency characteristic distribution of track irregularities and the distribution of instantaneous energy density in the sensitive wavelengths. The track geometry quality is evaluated based on the TFED, using track inspection data of actual high-speed railways. [ABSTRACT FROM AUTHOR]

Background: In cervical cancer, most patients die of metastasis. The epithelial-to-mesenchymal transition (EMT) is a pivotal and intricate process that increases the metastatic potential of cervical cancer. C-phycocyanin (C-PC) is a natural marine product isolated and purified from Spirulina platensis, has been investigated that has anti-cancer function. The aim of this study was to explore the inhibitory effect of C-phycocyanin on the migration and invasion of cervical cancer cells induced by transforming growth factor-β1 (TGF-β1), so as to provide a new idea for the treatment and prognosis of cervical cancer. Methods: A wound-healing assay, an invasion assay, immunofluorescence assay, western blot, flow cytometry and real-time reverse transcriptione polymerase chain reaction were explored in cervical cancer Caski cell lines. TGF-β/smad signaling pathway was evaluated of in Caski cell lines. Results: Our study indicated that TGF-β1 induced EMT in cervical cancer cells. C-phycocyanin inhibited EMT in Caski cells by down-regulating N-cadherin and up-regulating E-cadherin protein expression. Furthermore, C-phycocyanin could inhibit the expression and proteins Twist, Snail and Zeb1 transcription factors related to EMT. In addition, C-phycocyanin could inhibit the migration and invasion of Caski cells induced by TGF-β1. Besides, C-phycocyanin inhibited EMT through TGF-β/smads signaling pathway. We also found C-phycocyanin induced cell cycle G0/G1 arrest by decreasing protein expression levels of Cyclin D1 and p27. Conclusions: C-phycocyanin reversed TGF-β1-induced epithelial-to-mesenchymal transition in cervical cancer cells and down-regulated the TGF-β/samd signaling pathway induced G0/G1 arrest of tumor cell cycle. [ABSTRACT FROM AUTHOR]

Estimation of the single-index model with a discontinuous unknown link function is considered in this paper. Existed refined minimum average variance estimation (rMAVE) method can estimate the single-index parameter and unknown link function simultaneously by minimising the average pointwise conditional variance, where the conditional variance can be estimated using the local linear fit method with centred kernel function. When there are jumps in the link function, big biases around jumps can appear. For this reason, we embed the jump-preserving technique in the rMAVE method, then propose an adaptive jump-preserving estimation procedure for the single-index model. Concretely speaking, the conditional variance is obtained by the one among local linear fits with centred, left-sided and right-sided kernel functions who has minimum weighted residual mean squares. The resulting estimators can preserve the jumps well and also give smooth estimates of the continuity parts. Asymptotic properties are established under some mild conditions. Simulations and real data analysis show the proposed method works well. [ABSTRACT FROM AUTHOR]

Aims: Sirtuins connect energy generation and metabolic stress to the cellular acetylome. Currently, only the mitochondrial sirtuins (SIRT3-5) and SIRT1 have been shown to direct mitochondrial function; however, Aims: NAD-dependent protein deacetylase sirtuin-2 (SIRT2), the primary cytoplasmic sirtuin, is not yet reported to associate with mitochondria. Results: This study revealed a novel physiological function of SIRT2: the regulation of mitochondrial function. First, the acetylation of several metabolic mitochondrial proteins was found to be altered in Sirt2-deficient mice, which was, subsequently, validated by immunoprecipitation experiments in which the acetylated mitochondrial proteins directly interacted with SIRT2. Moreover, immuno-gold electron microscopic images of mouse brains showed that SIRT2 associates with the inner mitochondrial membrane in central nervous system cells. The loss of Sirt2 increased oxidative stress, decreased adenosine triphosphate levels, and altered mitochondrial morphology at the cellular and tissue ( i.e., brain) level. Furthermore, the autophagic/mitophagic processes were dysregulated in Sirt2-deficient neurons and mouse embryonic fibroblasts. Innovation: For the first time it is shown that SIRT2 directs mitochondrial metabolism. Conclusion: Together, these findings support that SIRT2 functions as a mitochondrial sirtuin, as well as a regulator of autophagy/mitophagy to maintain mitochondrial biology, thus facilitating cell survival. Antioxid. Redox Signal. 26, 849-863. [ABSTRACT FROM AUTHOR]

Track slabs are key components in high-speed railways, and it is crucial to detect the surface dimension deviation of track slabs manufactured as precast concrete. However, the traditional detection methods used to gauge track slabs are time consuming and costly. To overcome these limitations, this paper established a multi-tool-based design workflow for detection of the surface dimension deviation of track slabs. To investigate the feasibility of the proposed workflow, case studies assessed an automatic detection system with 3D scanning and robot technology for detecting track slabs. The experimental results of the case studies demonstrate that the proposed system can detect track slabs efficiently, stably, and accurately, thereby reflecting the potential application of the system in detecting the surface dimension deviation of the track slabs. Moreover, the automatic detection system can be conveniently extended to various industries to control the surface dimension deviations of diverse prefabricated cement components. • Proposed a design workflow of an automated fast track slab dimensional deviation detection system. • Planned the robot motion path and the scanning position, made the standard parts. • Constructed an evaluating and verification process of the system. • Significantly improved the detection efficiency with good stability and accuracy. [ABSTRACT FROM AUTHOR]

SUMMARY Through large-scale transformation analyses, TaMYB72 was identified as a flowering time regulator in wheat. TaMYB72 is a MYB family transcription factor localized to the nucleus. Three TaMYB72 homologs, TaMYB72-A, TaMYB72-B and TaMYB72-D, cloned from hexaploid wheat were mapped to the short arm of the group 6 chromosomes. Under the long-day conditions, over-expression of the TaMYB72 in rice shortened the flowering time by approximately 12 d. Expression analyses suggest that TaMYB72 may function through up-regulation of florigen genes Hd3a and RFT1. [ABSTRACT FROM AUTHOR]

A variable selection procedure based on least absolute deviation (LAD) estimation and adaptive lasso (LAD-Lasso for short) is proposed for median regression models with doubly censored data. The proposed procedure can select significant variables and estimate the parameters simultaneously, and the resulting estimators enjoy the oracle property. Simulation results show that the proposed method works well. [ABSTRACT FROM AUTHOR]

The satellite differential interferometric synthetic aperture radar (DInSAR) technology has been widely applied for mapping the ground deformation associated with the geophysical events such as earthquakes. However, the conventional DInSAR can measure only the one-dimensional (1D) ground displacement along the radar line of sight (LOS), and the crucial displacement measurements, e.g., near the epicenter and along the surface ruptures, are usually not available or degraded in quality due to the significant deformation gradients. With availability of satellite SAR images acquired along ascending and descending orbits, this paper proposes an integrated method to map the three-dimensional (3D) coseismic deformation field by combining DInSAR for detecting LOS displacements, the multiple aperture interferometry (MAI) for detecting along-track displacements, and the displacement gradient tensor (DGT) model for characterizing spatial correlation of ground displacements. The proposed method (termed as InSAR–DGT) was first tested through an experiment of recovering 3D displacements from a simulated coseismic deformation field. We then applied the proposed method to map the 3D coseismic deformation field related to the 2011 Tarlay earthquake (Myanmar) by using the ascending and descending ALOS PALSAR images. Both the results derived for the simulated experiment and the 2011 Tarlay earthquake show that the quality of the 3D coseismic displacements can be raised efficiently by the InSAR–DGT method, and the precisions in the east–west (E–W), north–south (N–S) and up–down (U–D) displacements for the 2011 Tarlay earthquake are increased 22%, 36% and 24%, respectively. The validation indicates that the improved coseismic deformation field for the 2011 Tarlay earthquake is in good agreement with the deformation field simulated from the existing optimized fault model. The number of the missing data points in the 3D coseismic deformation field can be reduced significantly by the InSAR–DGT method. It is revealed that the causative fault (i.e., the west part of the Nam Ma Fault) for the Tarlay earthquake generated a left-lateral slip that was accompanied by a minor normal dip-slip component. The careful interpretation demonstrates that the causative fault structures include the determined main fault segment and the two suspected branched segments at east of the Tarlay town. [ABSTRACT FROM AUTHOR]

Monitoring and modeling ground surface deformation are crucial for the dynamic assessment of geothermal resources and sustainable exploitation in a geothermal field. In this study, we extract the deformation in the Yangbajing geothermal field by the small baseline-synthetic aperture radar interferometry (SBAS-InSAR) method using 141 Sentinel-1A images collected between March 2017 and November 2021. The InSAR result indicates both uplift and subsidence in the geothermal field. Subsequently, we use a dual-source model combining a dipping ellipsoid and a rectangular surface to model the shallow reservoir that contracted to cause the complex subsidence field in the north of the geothermal field. The shallow reservoir that expanded to cause the uplift in the south is modeled by an ellipsoid source. The parameters inversion is processed by the nonlinear Bayesian inversion method which has been applied to search the optimal parameters setting in a priori space and evaluate the uncertainties by the confidence intervals. To validate our inversion results, we collect the data from 31 wells including extraction and injection wells, detailed tectonic survey data and geothermal isotherms of the Yangbajing geothermal field. The modeled shallow reservoir in the north is within a 140 °C ground isotherm and a 160 °C underground isotherm. The thickness and depth of the reservoir slightly exceed the data from producing wells, probably due to the structural subsidence of the reservoir. The geometric structure is consistent with the channel faults that control the formation and development of the shallow reservoirs. The modeled reservoir under the rebound area in the south is also validated by comparing the data. Furthermore, we estimate the volume loss and recovery of the contracting and expanding reservoirs. We analyse the deformation mechanisms by considering the tectonic formation, the reservoir structure, and the extraction and rechargeability of the reservoirs. This research suggests the deformation pattern of shallow porous reservoirs that have similar layer composition and tectonic structure elsewhere in the world. Moreover, it provides a theoretical model to explore the parameters and volume change of geothermal reservoirs in plateau-embedded basins around the world. Our work is significant for the conservation and development of geothermal energy in geothermal fields that experience deformation, both subsidence and uplift. [ABSTRACT FROM AUTHOR]

MYB-type proteins have been shown to participate in multiple stress responses. In the present study, we identified a gene in wheat induced by multiple abiotic stresses, TaMYB19, which encodes a R2R3-type MYB protein. Three highly homologous sequences of TaMYB19 were isolated from hexaploid wheat. Using the nulli-tetrasomic (NT) lines of Chinese Spring wheat, the three sequences were localized to chromosomes 1A, 1B and 1D and designated as TaMYB19-A, TaMYB19-B and TaMYB19-D, respectively. The expression patterns of these three genes were similar under different stress conditions. The TaMYB19-B sequence was selected for further analysis. The TaMYB19-B protein localized to the nucleus. A detailed characterization of Arabidopsis transgenic plants overexpressing the TaMYB19-B gene revealed that the TaMYB19-B protein could improve tolerance to multiple stresses during the seedling stage. We also found that the overexpression of TaMYB19-B resulted in changes in several physiological indices and altered the expression levels of a number of abiotic stress-related genes, allowing the plants to overcome adverse conditions. These results indicate that the TaMYB19 protein plays an important role in plant stress tolerance and that modification of the expression of this protein may improve abiotic stress tolerance in crop plants. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) takes a second and fourth position in the incidence and mortality lists respectively among all malignant tumors in urban populations in China. This study was designed to evaluate the cost-effectiveness of two different CRC screening protocols: faecal occult blood test (FOBT) alone, and FOBT plus a high-risk factor questionnaire (HRFQ) as the respective initial screens, followed by colonoscopy. We developed a Markov model to simulate the progression of a cohort of 100,000 average risk asymptomatic individuals moving through a defined series of states between the ages of 40 to 74 years. The parameters used for the modeling came from the CESP (Comparison and Evaluation of Screening Programs for Colorectal Cancer in Urban Communities in China) study and published literature. Eight CRC screening scenarios were tested in the Markov model. The cost-effectiveness of CRC screening under each scenario was measured by an incremental cost-effectiveness ratio (ICER) compared with a scenario without CRC screening. The study revealed that a combined use of FOBT and HRFQ is preferable in CRC screening programs as an initial screening instrument. Annual FOBT+HRFQ screening is recommended for those who have a negative initial result and those who have a positive result but have failed to continue to colonoscopic examination. Repeated colonoscopy (for those with a positive result in initial screening but a negative colonoscopy result) should be performed at a ten-year interval instead of one-year. Such a protocol would cost 7732 Yuan per life year saved, which is the most cost-effective option. In conclusion, the current Chinese Trial Version for CRC Screening Strategy should be revised in line with the most cost-effective protocol identified in this study. [ABSTRACT FROM AUTHOR]

Accurately detecting falls and providing clear directions for the fall can greatly assist medical staff in promptly developing rescue plans and reducing secondary injuries during transportation to the hospital. In order to facilitate portability and protect people's privacy, this paper presents a novel method for detecting fall direction during motion using the FMCW radar. We analyze the fall direction in motion based on the correlation between different motion states. The range–time (RT) features and Doppler–time (DT) features of the person from the motion state to the fallen state were obtained by using the FMCW radar. We analyzed the different features of the two states and used a two-branch convolutional neural network (CNN) to detect the falling direction of the person. In order to improve the reliability of the model, this paper presents a pattern feature extraction (PFE) algorithm that effectively eliminates noise and outliers in RT maps and DT maps. The experimental results show that the method proposed in this paper has an identification accuracy of 96.27% for different falling directions, which can accurately identify the falling direction and improve the efficiency of rescue. [ABSTRACT FROM AUTHOR]

Abstract: The German satellite TerraSAR-X (TSX) is able to provide high-resolution synthetic aperture radar (SAR) images for mapping surface deformation by the persistent scatterer interferometry (PSI) technique. To extend the application of PSI in detecting subsidence in areas with frequent surface changes, this paper presents a method of TSX PSI on a network of natural persistent scatterers (NPSs) and artificial corner reflectors (CRs) deployed on site. We select a suburban area of southwest Tianjin (China) as the testing site where 16 CRs and 10 leveling points (LPs) are deployed, and utilize 13 TSX images collected over this area between 2009 and 2010 to extract subsidence by the method proposed. Two types of CRs are set around the fishponds and crop parcels. 6 CRs are the conventional ones, i.e., fixed CRs (FCRs), while 10 CRs are the newly-designed ones, i.e., so-called portable CRs (PCRs) with capability of repeatable installation. The numerical analysis shows that the PCRs have the higher temporal stability of radar backscattering than the FCRs, and both of them are better than the NPSs in performance of radar reflectivity. The comparison with the leveling data at the CRs and LPs indicates that the subsidence measurements derived by the TSX PSI method can reach up to a millimeter level accuracy. This demonstrates that the TSX PSI method based on a network of NPSs and CRs is useful for detecting land subsidence in cultivated lands. [Copyright &y& Elsevier]

The aim of this study was to investigate the distribution, density, community structure and biodiversity characteristics of benthic diatoms, and to analyze whether differences in species composition and abundance exist in different regions of the Niyang River, Tibet. Among the 157 taxa observed in 15 sampling sites in the main river and tributary, most were casual species (>100), the relative abundance of the genera Achnanthes and Fragilaria was 67% of the total relative abundance. Achnanthes minutissima was the most important species and dominated the whole river reaches (average relative abundance was 30%); the average diatom densities were 7.4 × 10 cell/cm at all sites, and increased slowly from the upper section to downriver. The significant indicator taxa with higher relative abundance were Achnanthes biasolettiana (18.0%) and Fragilaria arcus (18.2%), Fragilaria capucina var. vaucheriae (31.2%), Fragilaria construens var. venter (11.3%) and Cymbella affinis (11.0%) in the upper, tributary and mid-river sections, respectively. Achnanthes minutissima was the most abundant species (56%) in the downriver section. Biodiversity indices showed a gradual decrease from the up- to down-river section, and dominant species were more abundant in the upper and mid-river sections than in the downriver section. A two-way indictor species analysis (TWINSPAN) of diatom composition clearly showed four different groups, namely the upper, mid, lower and tributary sections. Detrended correspondence analysis (DCA) supported the results of TWINSPAN, and the characteristics of site distribution and species composition in the Niyang River supported the spatial structure of diatom assemblages. This study indicates that bio-assessment programs utilizing benthic diatoms could clearly benefit lotic water with regional stratification. [ABSTRACT FROM AUTHOR]

Abstract: The Ms8.0 Wenchuan earthquake (in China) occurred on 12 May 2008 as a result of slip on the northeastern-striking Longmen Shan (LMS) faults beneath the rugged margin between the Qinghai-Tibet Plateau and Sichuan Basin. The catastrophic event caused significant surface ruptures and permanent ground displacement in a wide area. This paper concentrates on mapping surface deformation caused by the main shock with the interferometric synthetic aperture radar (InSAR) technology. The coseismic interferogram covering an area of over 83,000km2 is computed with use of 46 SAR images that were collected along 6 adjacent ascending orbits by the L-band SAR sensor onboard the Japanese Advanced Land Observing Satellite (ALOS). The displacements measured at 16 GPS sites are used to check the accuracy of the InSAR deformation measurements. The radar coherence is computed and analyzed in relation to the topography and the normalized difference vegetation index (NDVI) estimated from the Landsat-7 imagery. The results show that the coseismic surface deformation can be mapped up to a centimeter-accuracy level even over the highly mountainous and heavily vegetated area with the L-band interferometer. It is also demonstrated that the L-band interferograms with time interval of months to years can still maintain acceptable radar coherence for deformation extraction over the area under the extreme conditions. The extracted InSAR deformation measurements show that the lands in the Sichuan Basin had moved 0.1–1.3m toward the satellite along the radar line of sight (LOS) direction with an azimuth of 349.8° and an elevation angle of 51.3°, while the lands in the LMS area had moved 1.4m at most away from the satellite. [ABSTRACT FROM AUTHOR]

Abstract: A method for tightly integrating GPS observations and the persistent scatterer (PS) interferometric synthetic aperture radar (InSAR) is proposed to detect vertical ground motion in Hong Kong, China. The tropospheric zenith wet delays (ZWD) derived from GPS observations at sites in the SAR scenes are used first to model and correct for the tropospheric effects in the interferograms generated from the SAR images. The vertical motion rates (VMR) of the GPS sites determined based on the continuous GPS observations obtained at the sites are then used as constraints in the PS InSAR solutions to further enhance the quality of the solutions. Data from 12 continuous tracking GPS sites in Hong Kong and 8 ENVISAT ASAR images acquired during 2006–2007 are used to demonstrate the application of the proposed method. The results from the example show that the method is capable of detecting accurately the vertical ground motion. [ABSTRACT FROM AUTHOR]

Carbon dioxide sequestration in a coal-bed is a profitable method to reduce the concentration of greenhouse gas in the atmosphere and to recover byproduct methane from the coal seam. The important factor to be considered is the stability of the coal-bed with the increased carbon dioxide injection. It is crucial to avoid carbon dioxide escaping from the coal seam caused by structural deformation. Meanwhile, structural deformation also depends on such properties of the geological coal basin as fracture state and phase equilibrium, especially the porosity, permeability and saturation of the coal seam. In this study, a structural deformation effect was simulated with the purpose of predicting carbon dioxide storage in the environment of a typical unmineable coal seam. As an example, Appalachian Basin is considered in the deformation analysis of carbon dioxide sequestration based on the variable saturation model. Moreover, the comparison between simulations with and without the account of structural deformation is given. The results indicate that modeling of structural deformation in carbon sequestration is feasible by directly coupling structure terms to a variable saturated model. Moreover, introducing structural deformation effects into carbon sequestration modeling is important because it affects the fluid flow and leads to a faster drop of the resulting capillary pressure and relative permeability of the gas phase. This faster drop directly results in the diminished carbon dioxide storage capacity in a coal-bed basin. In addition, structural deformation modeling in carbon sequestration simulations can provide important insights into how to avoid carbon leakage and seepage by monitoring the effective stress and displacement of coal-bed basin during carbon dioxide injection. [Copyright &y& Elsevier]

Storage of carbon dioxide in deep coal seams is a profitable method to reduce the concentration of green house gases in the atmosphere while the methane as a byproduct can be extracted during carbon dioxide injection into the coal seam. In this procedure, the key element is to keep carbon dioxide in the coal seam without escaping for a long term. It is depended on many factors such as properties of coal basin, fracture state, phase equilibrium, etc., especially the porosity, permeability and saturation of the coal seam. In this paper, a variable saturation model was developed to predict the capacity of carbon dioxide sequestration and coal-bed methane recovery. This variable saturation model can be used to track the saturation variability with the partial pressures change caused by carbon dioxide injection. Saturation variability is a key factor to predict the capacity of carbon dioxide storage and methane recovery. Based on this variable saturation model, a set of related variables including capillary pressure, relative permeability, porosity, coupled adsorption model, concentration and temperature equations were solved. From results of the simulation, historical data agree with the variable saturation model as well as the adsorption model constructed by Langmuir equations. The Appalachian basin, as an example, modeled the carbon dioxide sequestration in this paper. The results of the study and the developed models can provide the projections for the CO2 sequestration and methane recovery in coal-beds within different regional specifics. [Copyright &y& Elsevier]

Investigates the accumulating ground settlement at the Chek Lap Kok International Airport using satellite synthetic aperture radar (SAR) interferometry in Hong Kong, China. Reclamation of the land occupied by the airport from the sea; Use of a pair of ERS-2 SAR images; Background of interferometric SAR; Outline of the data processing methods.

Commercial scale decarbonization through carbon capture and storage may likely involve many CO2 storage projects located in close proximity. The close proximity could raise concerns over caprock integrity associated with reservoir pressure buildup and interference among adjacent projects. Commercial-scale injection will also require large prospective CO2 storage resource and high injectivity in the targeted storage formations. To accommodate the need for both large resource and high injectivity, project operators could consider injecting CO2 into a stacked sequence of formations. This analysis investigates the benefits of injecting CO2 into a vertically stacked sequence of saline formations, over injecting the same amount of CO2 into a single saline formation, in addressing these challenges. Our analysis shows that injecting into the stacked sequence mitigates the extent of pressure buildup among the stacked formations, while still achieving the same or greater target CO2 storage volumes. Among cases modeled, the resulting pressure buildup front is most reduced when each storage site distributes injection volumes over several wells, each of which injects a portion of the total CO2 mass across the stacked sequence. This favorable case not only results in the smallest CO2 aerial footprint, but also shows the largest reduction in the pressure buildup at the top of perforation at the injection wells (upwards of approximately 46% compared to the single-formation storage), the result of which is crucial to maintain caprock integrity. This analysis provides insights into required decision-making when considering multi-project deployment in a shared basin. [ABSTRACT FROM AUTHOR]

Current research on deep learning-based intelligent landslide detection modeling has focused primarily on improving and innovating model structures. However, the impact of terrain factors and data fusion methods on the prediction accuracy of models remains underexplored. To clarify the contribution of terrain information to landslide detection modeling, 1022 landslide samples compiled from Planet remote sensing images and DEM data in the Sichuan–Tibet area. We investigate the impact of digital elevation models (DEMs), remote sensing image fusion, and feature fusion techniques on the landslide prediction accuracy of models. First, we analyze the role of DEM data in landslide modeling using models such as Fast_SCNN, the SegFormer, and the Swin Transformer. Next, we use a dual-branch network for feature fusion to assess different data fusion methods. We then conduct both quantitative and qualitative analyses of the modeling uncertainty, including examining the validation set accuracy, test set confusion matrices, prediction probability distributions, segmentation results, and Grad-CAM results. The findings indicate the following: (1) model predictions become more reliable when fusing DEM data with remote sensing images, enhancing the robustness of intelligent landslide detection modeling; (2) the results obtained through dual-branch network data feature fusion lead to slightly greater accuracy than those from data channel fusion; and (3) under consistent data conditions, deep convolutional neural network models and attention mechanism models show comparable capabilities in predicting landslides. These research outcomes provide valuable references and insights for deep learning-based intelligent landslide detection. [ABSTRACT FROM AUTHOR]

Epilithic green algae play crucial roles in aquatic ecosystems. While traditional morphological approaches have provided valuable insights into these algae, their limitations in resolving cryptic species and fully capturing the extent of diversity have impeded a comprehensive understanding. The diversity and phylogenetic relationships of these algae largely remain unexplored. In the present study, single molecular real-time (SMRT) sequencing of the full-length 18S rDNA was employed to investigate the molecular diversity and phylogenetic relationships of epilithic green algae in biodiversity conservation hotspots. A total of 79 709 algal reads were generated, yielding 169 amplicon sequence variants (ASVs) from 21 epilithic riverine green algal assemblages classified in the Ulvophyceae, Chlorophyceae and Trebouxiophyceae. The 10 families in which the greatest number of unique ASVs (diversity) were observed were the Ulvellaceae, Protosiphonaceae, Chlorococcaceae, Watanabeaceae, Chlorellaceae, Neochloridaceae, Chaetophoraceae, Hazeniaceae, Tupiellaceae and Scenedesmaceae. Unique clades formed by a substantial number of sequences of green algae were detected within the Ulvales/Ulotrichales (Ulvophyceae) and the Chlorococcaceae/Protosiphonaceae (Chlorophyceae). This study has unveiled hidden diversity within epilithic green algae, expanding our knowledge of their evolutionary relationships and providing fundamental data for taxonomic investigations within this group, as well as contributing to the assessment of algal diversity in biodiversity conservation hotspots. This study suggests that these epilithic green algal assemblages may be significantly more diverse than previously recognized, but we acknowledge the limited ecological and temporal scope of our sampling effort and the resulting effects on which taxa are identified, warranting further research. Molecular analysis shows high hidden diversity of epilithic green algae The families Ulvellaceae and Protosiphonaceae had the greatest number of unique ASVs Many unique clades within the Ulvales/Ulotrichales and Chlorococcaceae/Protosiphonaceae [ABSTRACT FROM AUTHOR]

Members of the family Scenedesmaceae are some of the most common algal taxa in inland ecosystems, and they are widely distributed in freshwaters, aerial, and sub-aerial habitats. With the continuous updating of methods, the classic morphological taxonomy of this family needs to be revised. In recent years, many genera of Scenedesmaceae have been established via the use of molecular methods. The phylogenetic relationships within Scenedesmaceae were analyzed using different molecular markers and morphological data, and the new freshwater genus Coccoidesmus Wang, Hou et Liu gen. nov. was described. Two new species in this genus were also described. Phylogenetic analysis based on tufA genes revealed that the new genus formed an independent clade closely related to Comasiella. However, these two genera are characterized by significant morphological differences in colony arrangement and cell shape. The chloroplast genome of the type species was assembled and annotated, and analyses of genome structure and sequences were conducted. More genome data could help clarify the phylogenetic relationships within this family. [ABSTRACT FROM AUTHOR]

As an approach with great potential, the interpretation of space-borne synthetic aperture radar (SAR) images has been applied for monitoring the dynamic evolution of the glacial lakes in recent years. Considering unfavorable factors, such as inherent topography-induced effects and speckle noise in SAR images, it is challenging to accurately map and track the dynamic evolution of the glacial lakes by using multi-temporal SAR images. This paper presents an improved neighborhood-based ratio method utilizing a time series of SAR images to identify the boundaries of the glacial lakes and detect their spatiotemporal changes. The proposed method was applied to monitor the dynamic evolution of the two glacial lakes with periodic water discharge at the terminus of the Gongba Glacier in the southeastern Tibetan Plateau by utilizing 144 Sentinel-1A SAR images collected between October of 2014 and November of 2020. We first generated the reference intensity image (RII) by averaging all the SAR images collected when the water in the glacial lakes was wholly discharged, then calculated the neighborhood-based ratio between RII and each SAR intensity image, and finally identified the boundaries of the glacial lakes by a ratio threshold determined statistically. The time series of areas of the glacial lakes were estimated in this way, and the dates for water recharging and discharging were accordingly determined. The testing results showed that the water of the two glacial lakes began to be recharged in April and reached their peak in August and then remained stable dynamically until they began to shrink in October and were discharged entirely in February of the following year. We observed the expansion process with annual growth rates of 3.19% and 12.63% for these two glacial lakes, respectively, and monitored a glacial lake outburst flood event in July 2018. The validation by comparing with the results derived from Sentinel-2A/B optical images indicates that the accuracy for identifying the boundaries of the glacial lakes with Sentinel-1A SAR images can reach up to 96.49%. Generally, this contribution demonstrates the reliability and precision of SAR images to provide regular updates for the dynamic monitoring of glacial lakes. [ABSTRACT FROM AUTHOR]

Coal fire disasters generally occur in major coal-producing countries. They destroyed many coal resources and triggered various environmental problems. The identification and state assessment of coal fire areas are paramount to coal fire management. In this paper, a method for identifying coal fires by integrating land surface temperatures (LSTs) from multitemporal thermal infrared remote sensing and subsidence information from multitemporal interferometric synthetic aperture radar (MT-InSAR) is proposed. The method primarily consists of estimating the LSTs and subsidence values, normalizing and equidistantly partitioning the LSTs, estimating the thermal anomaly frequency (TAF), extracting high-subsidence areas, determining the thermal anomaly frequency threshold (TAFT), and identifying coal fire areas according to the TAFT. The coal fire ratio index (CRI) was developed to quantitatively evaluate the severity of coal fires and its variations. Midong District, Urumqi, Xinjiang, China, was selected as the study area. Forty-five Landsat 8 images and sixty-one Sentinel-1 SAR images were used to retrieve LST and subsidence time series, respectively. The proposed method and CRI were applied to identify and evaluate coal fires in the study area. The results demonstrate the satisfactory reliability of these methods compared with field surveys. The maximum CRI was 6.145 × 10-4 (July 28, 2019), and the minimum CRI was 2.685 × 10-5 (January 13, 2020). Coal fires in summer were more severe than those in winter. The CRI profile presented seasonal and annual periodicities and was affected by the local climate. The soil cohesion and humidity are higher in winter due to possible snowmelt, which weakens the interaction between oxygen and coal seams and the subsequent combustion of coal. The LST, thermal anomaly, and deformation information were combined in a time series overlay analysis to reveal the differences in the LSTs and subsidence values among mining areas, coal fire areas, and areas with both mining and coal fires. The results verify the applicability and reliability of the proposed method. [ABSTRACT FROM AUTHOR]

Glacial lakes (GLs), a vital link between the hydrosphere and the cryosphere, participate in the local hydrological process, and their interannual dynamic evolution is an objective reflection and an indicator of regional climate change. The complex terrain and climatic conditions in mountainous areas where GLs are located make it difficult to employ conventional remote sensing observation means to obtain stable, accurate, and comprehensive observation data. In view of this situation, this study presents an algorithm with a high generalization ability established by optimizing and improving a deep learning (DL) semantic segmentation network model for extracting GL contours from combined synthetic-aperture radar (SAR) amplitude and multispectral imagery data. The aim is to use the high penetrability and all-weather advantages of SAR to reduce the effects of cloud cover as well as to integrate the multiscale and detail-oriented advantages of multispectral data to facilitate accurate, quantitative extraction of GL contours. The accuracy and reliability of the model and algorithm were examined by employing them to extract the contours of GLs in a large region of south-eastern Tibet from Landsat 8 optical remote sensing images and Sentinel-1A amplitude images. In this study, the contours of a total 8262 GLs in south-eastern Tibet were extracted. These GLs were distributed predominantly at altitudes of 4000–5500 m. Only 17.4% of these GLs were greater than 0.1 km2 in size, while a large number of small GLs made up the majority. Through analysis and validation, the proposed method was found highly capable of distinguishing rivers and lakes and able to effectively reduce the misidentification and extraction of rivers. With the DL model based on combined optical and SAR images, the intersection-over-union (IoU) score increased by 0.0212 (to 0.6207) on the validation set and by 0.038 (to 0.6397) on the prediction set. These validation data sufficiently demonstrate the efficacy of the model and algorithm. The technical means employed in this study as well as the results and data obtained can provide a reference for research and application expansion in related fields. [ABSTRACT FROM AUTHOR]

Thaw consolidation of degrading permafrost is a serious hazard to the safety and operation of infrastructure. Monitoring thermal changes in the active layer (AL), the proportion of the soil above permafrost that thaws and freezes periodically, is critical to understanding the conditions of the top layer above the permafrost and regulating the construction, operation, and maintenance of facilities. However, this is a very challenging task using ground-based methods such as ground-penetrating radar (GPR) or temperature sensors. This study explores the integration of interferometric measurements from high-resolution X-band Synthetic Aperture Radar (SAR) images and volumetric water content (VWC) data from SoilGrids to quantify detailed spatial variations in active layer thickness (ALT) in Iqaluit, the territorial capital of Nunavut in Canada. A total of 21 SAR images from COSMO Sky-Med (CSK) were first analyzed using the freely connected network interferometric synthetic aperture radar (FCNInSAR) method to map spatial and temporal variations in ground surface subsidence in the study area. Subsequently, we built an ALT retrieval model by introducing the thaw settlement coefficient, which takes soil properties and saturation state into account. The subsidence measurements from InSAR were then integrated with VWC extracted from the SoilGrids database to estimate changes in ALT. For validation, we conducted a comparison between estimated ALTs and in situ measurements in the airport sector. The InSAR survey identifies several sites of ground deformation at Iqaluit, subsiding at rates exceeding 80 mm/year. The subsidence rate changes along the runway coincide with frost cracks and ice-wedge furrows. The obtained ALTs, ranging from 0 to 5 m, vary significantly in different sediments. Maximum ALTs are found for rock areas, while shallow ALTs are distributed in the till blanket (Tb), the intertidal (Mi) sediments, and the alluvial flood plain (Afp) sediment units. The intersection of taxiway and runway has an AL thicker than other parts in the glaciomarine deltaic (GMd) sediments. Our study suggests that combining high-resolution SAR imagery with VWC data can provide more comprehensive ALT knowledge for hazard prevention and infrastructure operation in the permafrost zone. [ABSTRACT FROM AUTHOR]

Multiple aperture interferometric synthetic aperture radar (MAI) can measure ground displacements along SAR track. However, MAI measurements may suffer from severe ionospheric error, especially for long-wavelength SAR sensors. This study presents a new approach, azimuth split-spectrum interferometry (AziSSI), to correct ionospheric errors in MAI measurements. The proposed method can straightforwardly resolve ionospheric phase delay by exploiting two subband MAI interferograms with different centroid frequencies. We utilized two groups of ALOS-1 PALSAR images, which cover the 2008 Wenchuan earthquake containing strong coseismic ground deformation and a stable coast region in Chile, respectively, to test the proposed method. Experimental results show that the AziSSI method can successfully recover the coseismic displacements induced by the Wenchuan earthquake and circumvent the azimuth stripes for the Chile case’s MAI measurements. The maximum ionosphere-induced azimuth shifts are about 2.2 m for the Wenchuan case and 2.5 m for the Chile case. We validated the correction performance of the AziSSI method with the Wenchuan case by comparing the compensated azimuth displacements with the simulated deformation from a forward fault slip model and coseismic global positioning system (GPS) measurements. The validations show that the deformation patterns after the ionospheric correction are consistent with the simulations of the sinistral slip of the causative fault. The root-mean-square error between the GPS and MAI measurements is reduced from 0.77 to 0.28 m before and after the ionospheric correction, indicating that AziSSI can significantly compensate ionospheric errors for MAI. [ABSTRACT FROM AUTHOR]

As one of the important biodiversity conservation areas in China, the ecosystem in the lower reaches of the Yarlung Zangbo River is fragile, and is particularly sensitive to global changes. To reveal the diversity pattern of phytoplankton, the metabarcode sequencing was employed in the Medog section of the lower reaches of the Yarlung Zangbo River during autumn 2019 in present study. The phytoplankton assemblies can be significantly divided into the main stem and the tributaries; there are significant differences in the phytoplankton biomass, alpha and beta diversity between the main stem and the tributaries. While both the main stem and the tributaries are affected by dispersal limitation, the phytoplankton assemblages in the entire lower reaches are primarily influenced by heterogeneous selection. Community dissimilarity and assembly process were significantly correlated with turbidity, electrical conductivity, and nitrogen nutrition. The tributaries were the main source of the increase in phytoplankton diversity in the lower reaches of the Yarlung Zangbo River. Such diversity pattern of phytoplankton in the lower reach may be caused by the special habitat in Medog, that is, the excessive flow velocity, and the significant spatial heterogeneity in physical and chemical factors between stem and tributaries. Based on the results and conclusions obtained in present study, continuous long-term monitoring is essential to assess and quantify the impact of global changes on phytoplankton. [ABSTRACT FROM AUTHOR]

The sensitivity of synthetic aperture radar (SAR) coherence has been applied in delineating the boundaries of alpine glaciers because it is nearly unaffected by cloud coverage and can collect data day and night. However, very limited work with application of SAR data has been performed for the alpine glaciers in the Qinghai-Tibetan Plateau (QTP) of China. In this study, we attempted to investigate the change of coherence level in alpine glacier zone and access the glacier boundaries in the QTP using time series of Sentinel-1A SAR images. The DaDongkemadi Glacier (DDG) in the central QTP was selected as the study area with land cover mainly classified into wet snow, ice, river outwash and soil land. We utilized 45 Sentinel-1A C-band SAR images collected during October of 2014 through January of 2018 over the DDG to generate time series of interferometric coherence maps, and to further extract the DDG boundaries. Based on the spatiotemporal analysis of coherence values in the selected sampling areas, we first determined the threshold as 0.7 for distinguishing among different ground targets and then extracted the DDG boundaries through threshold-based segmentation and edge detection. The validation was performed by comparing the DDG boundaries extracted from the coherence maps with those extracted from the Sentinel-2B optical image. The testing results show that the wet snow and ice present a relatively low level of coherence (about 0.5), while the river outwash and the soil land present a higher level of coherence (0.8–1.0). It was found that the coherence maps spanning between June and September (i.e., the glacier ablation period) are the most suitable for identifying the snow- and ice-covered areas. When compared with the boundary detected using optical image, the mean value of Jaccard similarity coefficient for the total areas within the DDG boundaries derived from the coherence maps selected around July, August and September reached up to 0.9010. In contrast, the mean value from the coherence maps selected around December was relatively lower (0.8862). However, the coherence maps around December were the most suitable for distinguishing the ice from the river outwash around the DDG terminus, as the river outwash areas could hardly be differentiated from the ice-covered areas from June through September. The correlation analysis performed by using the meteorological data (i.e., air temperature and precipitation records) suggests that the air temperature and precipitation have a more significant influence on the coherence level of the ice and river outwash than the wet snow and soil land. The proposed method, applied efficiently in this study, shows the potential of multi-temporal coherence estimation from the Sentinel-1A mission to access the boundaries of alpine glaciers on a larger scale in the QTP. [ABSTRACT FROM AUTHOR]

Phytoplankton are the main primary producers in aquatic ecosystems and play an important role in food web and geochemical cycles. Its diversity, community structure, and assembly process are influenced by several factors. Alpine lake ecosystems are relatively weak and extremely sensitive to global climate change. However, the impact of climate change on phytoplankton in Qinghai-Tibet Plateau lakes and their responses are still unclear. In this study, we analyzed the diversity, environmental drivers, and assembly process of phytoplankton community in the central QTP lakes. The phytoplankton of these lakes can be primarily distinguished into freshwater and brackish types, with significant differences in species diversity and community dissimilarity. Both shared nearly same key environmental factors that significantly affecting phytoplankton such as EC, and brackish lakes were also positively correlative with TN. Stochastic process was predominant in phytoplankton assembly. Additionally, freshwater and brackish lakes were dominated by dispersal limitation and heterogeneous selection respectively. Alpine lakes had significant EC thresholds, and their diversity and assembly processes changed significantly around the thresholds. The present findings have important implications for understanding and predicting the response of lake phytoplankton communities to climate change and for making decisions to protect the ecological resources of alpine lakes. [ABSTRACT FROM AUTHOR]

During our investigation of diatom biodiversity in Xizang, two species exhibited unique morphological features discriminative from all previously known genera. Herein we describe these two species and describe as new the genus, Spargeria gen. nov. The new genus features narrow to wide rectangular valves, narrow valve mantles, filiform raphe branches that occur on the valve face only, terminal raphe fissures straight or slightly deflected to same side, bow-tie shaped central areas, chambered striae present on the valve face only, being absent from the mantle, wider striae near the axial area and very narrow near the margin, multiseriate striae with small and round areolae that are occluded externally. Comparatively, Spargeria zhuii sp. nov. has larger and robust valves, radiate striae, with one divergent stria near the apices, while Spargeria chenia sp. nov. is smaller, with narrow valves, striae slightly radiate in the middle, becoming convergent or parallel near apices. This new genus belongs to the family Pinnulariaceae, and it was compared and contrasted with other genera of this family. Our work suggests the need for continued studies to document the biodiversity of diatoms in Xizang. [ABSTRACT FROM AUTHOR]

Interferograms with short wavelength (e.g., X-band) are usually prone to temporal decorrelation in permafrost regions, leading to the unavailability of sufficient high-coherence interferograms for performing conventional time series InSAR analysis. This paper proposes the utilization of temporary scatterers for the stacking InSAR method, thus enabling extraction of subsidence in a permafrost region with limited SAR images and limited high-coherence interferograms. Such method is termed as the temporary scatterers stacking InSAR (TSS-InSAR). Taking the Gonghe-Yushu highway (about 30 km), part of G214 National Highway in Qinghai province (in a permafrost region), as a case study, this TSS-InSAR approach was demonstrated in detail and implemented. With 10 TerraSAR-X images acquired during the period from May 2015 to August 2015, the subsidence along this highway was extracted. In this case the lack of a consistent number of SAR acquisitions limits the possibility to perform other conventional time series InSAR analysis. The results show that the middle part of this highway is in the thermokarst and seasonal frozen soil area, and its accumulated subsidence reach up to 10 cm in 110 days. The thawing phenomena is still the main reason for the instability of highway. The results demonstrate that the TSS-InSAR method can effectively extract the subsidence information in a challenging scenario with limited X-band SAR images and limited high-coherence interferograms, where other time series InSAR-based techniques cannot be applied in a simple way. [ABSTRACT FROM AUTHOR]

We consider the vulnerable option pricing problem when the stochastic interest rate is driven by a Hull-White model. Based on the firm value model, we suppose that the stock prices, assets and liabilities of a company follow the relevant O-U processes. We adopt the martingale approach to determine the equivalent martingale measure for pricing the vulnerable binary option, the analytical pricing formula of the vulnerable binary options is derived. [ABSTRACT FROM AUTHOR]

Background: Intrahepatic cholangiocarcinoma (ICC) accounts for about 15% of primary liver cancer, and the incidence rate has been rising in recent years. Surgical resection is the best treatment for ICC, but the 5-year survival rate is less than 30%. ICC signature genes are crucial for the early diagnosis of ICC, so it is especially important to find its signature genes and therapeutic drug. Here, we studied that bufalin targeting CAMKK2 promotes mitochondrial dysfunction and inhibits the occurrence and metastasis of intrahepatic cholangiocarcinoma through Wnt/β-catenin signal pathway. Methods: IC50 of bufalin in ICC cells was determined by CCK8 and invasive and migratory abilities were verified by wound healing, cell cloning, transwell and Western blot. IF and IHC verified the expression of CAMKK2 between ICC patients and normal subjects. BLI and pull-down demonstrated the binding ability of bufalin and CAMKK2. Bioinformatics predicted whether CAMKK2 was related to the Wnt/β-catenin pathway. SKL2001, an activator of β-catenin, verified whether bufalin acted through this pathway. In vitro and in vivo experiments verified whether overexpression of CAMKK2 affects the proliferative and migratory effects of ICC. Transmission electron microscopy verified mitochondrial integrity. Associated Ca2+ levels verified the biological effects of ANXA2 on ICC. Results: It was found that bufalin inhibited the proliferation and migration of ICC, and CAMKK2 was highly expressed in ICC, and its high expression was positively correlated with poor prognosis.CAMKK2 is a direct target of bufalin, and is associated with the Wnt/β-catenin signaling pathway, which was dose-dependently decreased after bufalin treatment. In vitro and in vivo experiments verified that CAMKK2 overexpression promoted ICC proliferation and migration, and bufalin reversed this effect. CAMKK2 was associated with Ca2+, and changes in Ca2+ content induced changes in the protein content of ANXA2, which was dose-dependently decreasing in cytoplasmic ANXA2 and dose-dependently increasing in mitochondrial ANXA2 after bufalin treatment. In CAMKK2 overexpressing cells, ANXA2 was knocked down, and we found that reversal of CAMKK2 overexpression-induced enhancement of ICC proliferation and migration after siANXA2. Conclusions: Our results suggest that bufalin targeting CAMKK2 promotes mitochondrial dysfunction and inhibits the proliferation and migration of intrahepatic cholangiocarcinoma through Wnt/β-catenin signal pathway. Thus, bufalin, as a drug, may also be used for cancer therapy in ICC in the future. [ABSTRACT FROM AUTHOR]

Makinoella Okada is a genus of coccoid green algae belonging to the family Oocystaceae with typical morphological characteristics. Reports to date included only one type species. Since the genus is rarely reported, there is a lack of taxonomic research. In this study, 17 strains of this genus were collected from several different places in China, and their taxonomic studies were conducted based on morphological and molecular phylogenetic analysis. The phylogenetic results based on the analysis of ITS, chloroplast genes rbcL and tufA showed that the genus was divided into two branches. One of the branches comprised newly collected algae. Compensatory base changes (CBCs) and hemi-compensatory base changes (hemi-CBCs) within the secondary structure of the ITS-2 confirmed the branches as two species. Compared with the type species of Makinoella tosaensis, the cell size of this new branch was only about 50%, and included 2–4 colonial cells. Therefore, based on the smaller cell size, simpler colony composition, independent phylogenetic position and CBCs and hemi-CBCs, we suggest that the new clade should be designated as a new taxon of Makinoella, namely Makinoella parva. Among the four molecular markers using in this study, the rbcL and newly introduced ITS are recommended for species separation, which can help further studies to revise the species and generic concepts of the family. [ABSTRACT FROM AUTHOR]

The green algal genus Aphanochaete consists of species with uniseriate, simple, or irregularly branched, prostrate, and erect filaments, with cells bearing unsheathed unicellular hairs with or without bulbous bases. In this study, 12 strains of Aphanochaete were isolated and successfully cultured and their phylogenetic relationships were determined using the morphological data, along with 18 S rDNA and a concatenated dataset of four markers (18 S + 5.8 S + ITS2 + partial 28 S rDNA). Within the genus Aphanochaete, three types of zoospore germination and two types of unicellular hairs distinguished all the clades of this genus, which was consistent with molecular phylogeny and the compensatory case changes in ITS2 secondary structures. Aphanochaete xiantaoensis was determined to be a new species owing to its unique unipolar zoospore germination, which clearly differed from bipolar or cruciate zoospore germination in other species. While molecular phylogeny indicated that the number of hairs per cell was the poor taxonomic characteristics, we propose to list A. polychaete as a synonym of A. repens. Phylogenetic analyses revealed that different species within the genus Aphanochaete might have evolved from bipolar zoospore germination toward cruciate and unipolar zoospore germination. [ABSTRACT FROM AUTHOR]

Pixel Offset Tracking (POT) for optical imagery is a widely used method for extracting large-scale ground deformation. However, the influence of imaging parameters on the measurement accuracy of POT is still unclear. In this study, based on 16 pairs of Sentinel-2 images covering the period before and after the Ms6.9 Menyuan earthquake in 2022, we quantitatively assessed the effects of imaging bands, time intervals between image pairs, and differences in solar zenith angles on the measurement accuracy of optical POT. The results showed that the quality of ground deformation extracted using the near-infrared band was superior to other bands. The accuracy of optical POT measurements exhibited a negative correlation with both the time interval between image pairs and the differences in solar zenith angles. The maximum difference in optical POT measurement accuracy for the near-infrared band between image pairs with different time intervals (5/10/15 days) reached 30.3%, while the maximum difference in deformation measurement accuracy for pairs with different solar zenith angle differences was 30.56%. Utilizing the optimal POT image pair, the accuracy of co-seismic deformation measurement for the Menyuan earthquake improved by 48.3% compared to the worst image pair. The maximum co-seismic horizontal displacement caused by the earthquake was estimated to be 3.00 ± 0.51 m. [ABSTRACT FROM AUTHOR]

• The topographic effects on NIRv-derived photosynthetic phenology were seasonally divergent. • The seasonal divergence of NIRv-derived photosynthetic phenology might be related to the contrasting velocities of the magnitude of topographic effects on NIRv around SOS and EOS. • The topographically corrected NIRv (TCNIRv) reduced topographic effects in the original NIRv and it was comparable to GPP in estimating SOS/EOS. Accurate estimation of photosynthetic phenology is of great importance for understanding the response of terrestrial biosphere to climate change. The near-infrared reflectance of vegetation (NIRv) has been increasingly used to estimate photosynthetic phenology. However, topography significantly affects illumination conditions and induces uncertainty in the retrieval of NIRv photosynthetic phenology over mountainous areas. We evaluated the illumination effects on three modalities of NIRv: (i) the original NIRv, (ii) the product of NIRv and solar incident radiation (NIRvP), and (iii) the topographically corrected NIRv (TCNIRv). We assessed the impact of sun geometry on the phenological metrics for the timing of the start and end of the season (i.e., SOS and EOS) derived from satellite NIRv time series as compared with those derived from in-situ gross primary production (GPP) measured at the Brasschaat (BE-Bra) and Lägeren (CH-Lae) flux towers located, respectively, over a flat and a mountainous forest area in Europe. We observed a seasonally divergent performance of NIRv in photosynthetic phenology extraction: NIRv-derived SOS had a good consistency with GPP-derived estimates (109/114d for NIRv vs 108/115d for GPP at BE-Bra/CH-Lae), whilst it showed a positive time lag for the EOS (291/292d for NIRv vs 264/268d for GPP at BE-Bra/CH-Lae). The radiation constraint in NIRvP formulation corrected the bias in NIRv-based EOS estimates. Path length correction (PLC) also alleviates the illumination effects on the original NIRv, making TCNIRv comparable to NIRvP in estimating SOS and EOS. We conclude that illumination effects must be corrected from NIRv for the extraction of photosynthetic phenology, especially for the autumn phenology. Our study has significant implications for understanding the responses of phenology to climate change and the climate-carbon feedbacks, particularly over complex topography mountainous areas. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) remote sensing technology has the advantage of all-weather observation and can acquire time-series images with crop growth period, which has great potential for applications such as crop phenology analysis. However, available studies primarily focus on conducting statistical and crop growth analyses based on the polarization or backscatter intensities of SAR images, and the exploration of polarization scattering information in SAR images is not sufficient. To comprehensively reflect the polarization characteristics and scattering mechanisms of crop at different growth stages, we propose a new method for extracting vegetation descriptors from Sentinel-1 dual-polarimetric SAR data. The method combines the backscattering intensity and polarization decomposition information to construct a normalized index q , which is used to generate three vegetation descriptors: the co-pol purity parameter (m cp ), the pseudo-scattering angle (θ cp ), and the pseudo-scattering entropy (H cp ). Further, a novel unsupervised clustering framework, founded on H cp and θ cp , has been proposed. This framework establishes six zones (named as Z1 to Z6) representing distinct physical scattering mechanisms, and by statistically sampling point data, it can determine the growth stage of the crops For validating the performance of the proposed vegetation descriptors and clustering framework, we conducted a three-year experiment using four crops from two publicly available datasets, namely wheat and canola from the Carman in Canada (Test site-1), corn and soybeans from Iowa in the United States (Test site-2). The experimental results indicate that m cp , θ cp , and H cp exhibit regular changes at different growth stages of crops from planting to maturity, with m cp and θ cp gradually decreasing while H cp gradually increasing. Within the entire phenology window, θ cp changes by approximately 42°, while both m cp and θ cp varies by about 0.9, and the sampling points shift from the Z2 to the Z5 zone. The vegetation descriptors are highly sensitive to the growth status of crops, and the clustering framework can also effectively respond to different growth stages of vegetation. Furthermore, the vegetation descriptors and clustering framework proposed in this study have the potential for extended application to different crop types and other polarimetric SAR data sources. [ABSTRACT FROM AUTHOR]

The World Health Organization states that the application of pit and fissure sealants (PFSs) is an effective way to prevent dental caries. Estimates of potential health and economic impacts of PFS upon school-age children provide crucial evidence to support the extension of PFS coverage to all target populations. The China Children's Oral Disease Comprehensive Intervention Project was launched in 2009 to provide free oral health examinations, PFS application, and oral health education for children aged 7 to 9 years. However, the national-level health and economic impacts of the program are unclear. To provide higher quality evidence at the national level in China, we developed a multi-perspective, multistate Markov model to estimate the cost and effect of PFS application to prevent dental caries. The total cost of the PFS project was 2.087 billion CNY, which can prevent 16.06 million PFMs from caries lesions. Compared with no intervention, PFS application was cost-effective from payer and society perspectives (BCR = 1.22 from the payer's perspective, BCR = 1.91 from the societal perspective). The incremental cost-effectiveness ratio from both perspectives was negative (−61.46 CNY from the payer's perspective, and −125.75 CNY from the societal perspective), indicating that PFS was cost-effective and cost-saving. Expanding the coverage of PFS application in school can be a more cost-effective strategy for caries prevention in China. [ABSTRACT FROM AUTHOR]

Background: Triple-negative breast cancer is a biological subtype of breast cancer, which is unresponsive to conventional chemotherapies and has a poor prognosis. C-Phycocyanin (C-PC), a marine natural purified from Spirulina platensis, has been investigated that has anti-cancer function. The mitogen activated protein kinase (MAPK) pathway plays a crucial role in the development and progression of cancer. Therefore, we would like to study the anti-cancer effects of C-phycocyanin in the treatment of triple-negative breast cancer, and explore the role of MAPK pathway in the anti-tumor effects of C-phycocyanin. Methods: Cell proliferation, cell cycle, cell apoptosis and cell migration were explored in breast cancer MDA-MB-231 cell lines. AKT, MAPK and membrane death receptor signaling were evaluated in MDA-MB-231 cell lines. Results: Our study indicated that C-phycocyanin inhibited cell proliferation and reduced colony formation ability of MDA-MB-231 cells. Furthermore, C-phycocyanin induced cell cycle G0/G1 arrest by decreasing protein expression levels of Cyclin D1 and CDK-2 and increasing protein expression levels of p21 and p27. In addition, C-phycocyanin induced cell apoptotic by activating cell membrane surface death receptor pathway. Besides, C-phycocyanin downregulated the protein expression levels of cyclooxygenase-2, and further inhibited MDA-MB-231 cells migration. We also found cell death induced by C-phycocyanin was carried through the MAPK signaling pathways. C-Phycocyanin was able to induce MDA-MB-231 cell apoptosis by activating p38 MAPK and JNK signaling pathways while inhibiting ERK pathway. Conclusions: C-Phycocyanin exerted anti-cancer activity via the MAPK signaling pathway in MDA-MB-231 cells. [ABSTRACT FROM AUTHOR]