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Time-series ground deformation monitoring and reservoir parameter inversion are crucial for the dynamic assessment of oilfield resources and sustainable exploitation in oilfields. As some of the regions with the richest oil reserves in China, the oilfield areas in the western Qaidam Basin were selected as a typical study area. Firstly, we used SAR images collected by the Sentinel-1A satellite from January 2021 to December 2022 and applied the multidimensional small baseline subset (MSBAS) method to obtain vertical and east–west deformation measurements. On this basis, a nonlinear Bayesian inversion method was applied to model the shallow reservoir in a series of complex deformation areas, based on a single-source model and a multi-source model, respectively. As a result, the ground deformation monitoring results obtained by long time-series InSAR clearly reflect the uneven ground deformation caused by the oil extraction and water injection operation processes. There was slight subsidence in the Huatugou oilfield, while significant uplift deformation occurred in the Ganchaigou oilfield and the Youshashan oilfield, with a maximum uplift rate of 48 mm/year. Further analysis indicated that the introduction of the 2D deformation field helps to improve the robustness of oilfield reservoir parameter inversion. Moreover, the dual-source model is more suitable than the single-source model for inverting reservoir parameters of complex deformation. This study not only fills the gap of InSAR deformation monitoring for the oilfields in the western Qaidam Basin but also provides a theoretical reference for the model and method selection of reservoir parameter inversion in other oilfields.

The characteristics of active fault movements are essential for estimating the earthquake potential on the Tibetan Plateau (TP) in a complex geological setting. The 2022 Menyuan Mw6.7 earthquake was studied by a joint seismological and geodetic methodology to deepen the scientific understanding of the source parameters and deformation mechanisms. Firstly, the entire InSAR co-seismic deformation field is obtained based on ascending and descending Sentinel-1A imagery. Subsequently, a Bayesian algorithm is applied in fault geometry and slip distribution determination by combining InSAR measurements and teleseismic data. And the fault movement characteristics of the 2022 Menyuan earthquake are analyzed. Finally, a comprehensive “surface-subsurface" analysis of the effects caused by this earthquake was carried out by combining InSAR and fault data. The results demonstrate that the ground settlement and uplift induced by the 2022 Menyuan earthquake are significant, with a maximum relative deformation of 56 cm. The seismogenic fault is on the junction of the Lenglongling (LLL) and Tuolaishan (TLS) faults, and the main body is in the western part of the LLL fault, a high dip left-lateral strike-slip fault with NWW-SEE strike. The slip distribution results indicate that the largest slip of 3.45 m occurs at about 5 km below the ground, and the earthquake magnitude is Mw6.63. And further analysis by integrated geological structure and inversion results reveals that the earthquakes that occurred on the North Lenglongling Fault (NLLL) in 1986 and 2016 have contributed to the 2022 Menyuan earthquake.

Previous wildfire risk assessments have problems such as subjectivity of weight allocation and the linearization of statistical models, resulting in generally low robustness and low generalization ability of fire risk assessment models. Therefore, in this paper, we explored the potential of integration machine learning algorithms to build wildfire risk assessment models. Based on analyzing fire data’s spatial and temporal distribution, we selected 10 triggering factors of topography, meteorology, vegetation, and human activities, using frequency ratio (FR) to provide uniform data representation of triggering factors. Next, we used the Bayesian optimization (BO) algorithm to perform hyperparametric optimization solutions for various machine learning models: support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost). Finally, we constructed an integration machine learning algorithm to acquire a fire risk grading map and the importance evaluation corresponding to each triggering factor. For validation purposes, we selected Liangshan Prefecture in Sichuan Province as the specific study area and obtained MCD64A1 burned area product to extract the extent of burned areas in Liangshan Prefecture from 2011 to 2020. The accuracy, kappa coefficient, and area under curve (AUC) were then applied to assess the predictive power and consistency of the fire risk classification maps. The experimental analysis showed that among the three models, FR-BO-XGBoost had the best performance in wildfire risk assessment in the Liangshan region (AUC = 0.887), followed by FR-BO-RF (AUC = 0.876) and FR-BO-SVM (AUC = 0.820). The feature importance result indicated that the study area’s most significant effects on wildfires were precipitation, NDVI, land cover, and maximum temperature. The proposed method avoided the subjective weighting and model linearization problems. Compared with the previous methods, it automatically acquired the importance of the triggering factors to the wildfire, which had certain advantages in wildfire risk assessment, and was worthy of further promotion.

The mountainous area of southwest China is characterized by significant topography and complex geological conditions, which pose great challenges to the airport’s site selection, construction, and safe operation. Suining Anju Airport, one of the key projects under construction in southwest China, is essential in alleviating and dredging the air passenger flow in Sichuan Province. Because the overlying quaternary strata’s physical and mechanical properties, thickness, and distribution range are fairly different in the longitudinal and transverse directions, the Anju Airport’s foundation in the hilly area has typical inhomogeneity. Large-scale excavation and filling pose a challenge to the ground stability of the airport. To comprehensively monitor Anju Airport’s uneven ground subsidence during the construction period, this paper selected SAR image data collected by the Sentinel-1A satellite from May 2018 to June 2021 to extract time-series ground subsidence measurements based on the SBAS-InSAR method. Furthermore, based on the simulation of roadbed filling in the airport’s parallel slide fill area, the dynamic evolution analysis of soil stress field and internal subsidence caused by roadbed filling activities was carried out to further reveal the occurrence mechanism of ground subsidence. The monitoring results show that the subsidence centers of Anju Airport are mainly distributed in the filling areas, and the average annual subsidence is −20~−75 mm/yr from May 2018 to June 2021. Comparative analysis with in situ data indicates that the RMSE of InSAR monitoring results was ±6.12 mm. The numerical simulation shows that the subsidence of the airport parallel slide is mainly caused by a load of subgrade filling body and the compression of its weight. The results of this study can provide reference methodology and data support for the construction and future safe operation of Suining Anju Airport.

Vegetation net primary productivity (VNPP) is the main factor in ecosystem carbon sink function and regulation of environmental processes. However, NPP data products have data missing in some areas, which affects the availability and overall accuracy level of data. Therefore, we adopted the Factor Analysis Backpropagation neural network model (FA-BP model) to acquire a high-accuracy and high-reliability NPP result without missing or empty areas by using a series of easily accessible datasets, such as meteorological data and remote sensing data. We selected the western Sichuan region as the study area and carried out a VNPP time series estimation from 2000 to 2016. Comparative simulations also verify the accuracy of the time series estimation results: The Pearson correlation r of VNPP prediction results ranged from 0.807 to 0.917, the mean absolute error ranged from 29.1 to 38.9, the root mean square error was between 37.3 and 51.8, and the mean relative error varies from 0.10 to 0.14. Further analysis shows that the spatial pattern of estimated VNPP during the past 17 years in western Sichuan shows a decreasing trend from southeast to northwest. Besides, the VNPP time series is generally on an upward trend in this period. The increasing and decreasing areas of VNPP values in the study area accounted for 81.42% and 18.58%, respectively. Moreover, we find that temperature dominates the change of VNPP in the whole western Sichuan region. The data processing method and experimental results presented in this paper can provide a reference for accurately acquiring VNPP and related studies on natural resources and climate change.

Compared with previous snow depth monitoring methods, global navigation satellite system-interferometric reflectometry (GNSS-IR) technology has the advantage of obtaining continuous daily observation data, and has great application potential. However, since GNSS satellites are in motion, their position in the sky is constantly varying, and the Fresnel reflection areas about the receiver in different periods alter accordingly. As a result, the retrieving results obtained from different GNSS satellites, and data sets collected in different periods, fluctuate considerably, making the traditional single-satellite-based GNSS-IR retrieving method have limitations in accuracy and reliability. Therefore, this paper proposed a novel GNSS-IR signal-to-noise ratio (SNR) retrieving snow depth method for fusing the available GNSS-IR observations to obtain an accurate and reliable result. We established the retrieval model based on the backpropagation algorithm, which makes full use of the back propagation (BP) neural network’s self-learning and self-adaptive capability to exploit the degree of contribution of different satellites to the final results. Then, the SNR observations of the global positioning system (GPS) L1 carrier from the Plate Boundary Observation (PBO) site P351 were collected to experiment for validation purposes. For all available GPS L1 carrier data, the snow depth values retrieved for each satellite were first obtained by the existing single-satellite-based GNSS-IR retrieval method. Then, four groups of comparison results were acquired, based on the multiple linear regression model, random forest model, mean fusion model, and the proposed BP neural network model, respectively. Taking the snow depth in-situ data provided by snow telemetry (SNOTEL) as a reference, the root mean squared error (RMSE) and mean absolute error (MAE) of the proposed solution are 0.0297 m and 0.0219 m, respectively. Furthermore, the retrieving results are highly consistent with the measured data, and the correlation coefficient is 0.9407.

IntroductionImpaired lung function is independently associated with higher rates of disability, however, few studies have examined the association between lung function and functional limitation. This study aimed to assess this association and dose-response relationship in older adults.MethodsData from the National Health and Nutrition Examination Survey (2007-2012) was used as a cross-sectional study. Lung function was determined by Forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC). Functional limitation in older adults was identified by six self-reported questions on physical function. 3070 adults aged 60 and over were enrolled in our study. Logistic regression models and restricted cubic spline models were applied to examine the association between lung function and the risk of functional limitation.ResultsFEV1 and FVC were inversely associated with the risk of functional limitation. In the full adjusted model, compared with the lowest tertile of FEV1, the odds ratios (95% confidence intervals) of functional limitation for tertile 2 and tertile 3 were 0.5422 (0.3848-0.7639) and 0.4403 (0.2685-0.7220), and the odds ratios (95% confidence intervals) of functional limitation for tertile 2 and tertile 3 of FVC were 0.5243 (0.3503-0.7848) and 0.3726 (0.2072-0.6698). Furthermore, an inverse association persisted after stratified analysis by gender and sensitivity analysis. Dose-response analyses showed that the odds of functional limitation declined with increase in FEV1 and FVC in a nonlinear manner.ConclusionsLung function was inversely associated with functional limitation among older adults.

Abstract Wnt/β-catenin signaling is a critical pathway that influences development and therapeutic response of non-small cell lung cancer (NSCLC). In recent years, many Wnt regulators, including proteins, miRNAs, lncRNAs, and circRNAs, have been found to promote or inhibit signaling by acting on Wnt proteins, receptors, signal transducers and transcriptional effectors. The identification of these regulators and their underlying molecular mechanisms provides important implications for how to target this pathway therapeutically. In this review, we summarize recent studies of Wnt regulators in the development and therapeutic response of NSCLC.

Background and Objectives: Few studies have investigated the effects of dietary theobromine intake on the cognitive performance of older adults. Therefore, we investigated these effects in older adults in the United States. Methods and Study Design: In this cross-sectional study, we used data (2011–2014) from the National Health and Nutrition Examination Survey. Intake of theobromine intake was obtained through two 24-h dietary recall interviews and was adjusted by energy. Cognitive performance was assessed using the animal fluency test, Consortium to Establish a Registry for Alzheimer’s Disease Word Learning subtest (CERAD), and Digit Symbol Substitution Test (DSST). Logistic regression and restricted cubic spline models were constructed to evaluate the correlation between the dietary intake of theobromine from different sources and the likelihood of low cognitive performance. Results: The fully adjusted model revealed that compared with the lowest quintile, the odds ratios (with 95% confidence intervals) of cognitive performance in the CERAD test were 0.42 (0.28–0.64), 0.34 (0.14– 0.83), 0.25 (0.07–0.87), and 0.35 (0.13–0.95) for the highest quintile of total theobromine intake and that from chocolate, coffee, and cream, respectively. Dose–response relationship analysis indicated nonlinear correlations between the likelihood of low cognitive performance and dietary theobromine (total intake and that from chocolate, coffee, and cream). An L-shaped relationship was observed between total theobromine intake and cognitive performance in the CERAD test. Conclusions: The dietary intakes of theobromine (total and that from chocolate, coffee, and cream) may protect older adults, particularly men, against low cognitive performance. [ABSTRACT FROM AUTHOR]

Objective To identify the specificity of alloantibody against high-frequency antigens in one case suffering with severe hemolytic diseases of the fetus and newborn (HDFN) and to screen for matching blood for transfusion. Methods The HDFN test and the antibody serological identification tests in the mother were performed. Several common high frequency antigens of maternal red blood cells (RBCs) were determined. IgG subtype coated on the RBCs of the newborn was determined. The phagocytic efficiency of the antibody was tested using the monocyte phagocytosis of sensitized erythrocyte by flow cytometry in vitro. Sanger sequencing of DI gene was performed in the mother, father and mother’s brother. The diluted maternal plasma was used for large scale screening of matching blood using IAT in Coomb’s gel card. Results Di(b-) phenotype was identified in the mother of the newborn and anti-Dib (titer: 512) related HDN was detected in the newborn. IgG1 and IgG2 subtypes of anti-Dib were detected and the rate of monocyte phagocytosis was 88.83%(74.7/84.09). The compatible blood was not detected in the maternal relatives. Subsequently, the newborn received the matching RBCs of two Di(b-) donors identified from 5 520 blood donors and discharged from the hospital. We screened out 17 Di(b-) donors out of 51 334 blood donors, indicating that the distribution frequency of Di(b-) among blood donors in Guangzhou was about 0.033% (17/51 334). Conclusion By serology and molecular biology methods, the newborn was identified with HDFN caused by anti-Dib, and an effective large-scale screening method for Di (b -) rare blood types was established to find matching blood, which supported the establishment of rare Di(b-) blood database.

This study utilized a plant-wearable sap flow sensor developed by a multidisciplinary team at Zhejiang University to monitor water distribution patterns in watermelon fruit stalks throughout their developmental stages. The dynamic rules of sap flow at different stages of fruit development were discovered: (1) In the first stage, sap flow into the fruit gradually halts after sunrise due to increased leaf transpiration, followed by a rapid increase post-noon until the next morning, correlating with fruit expansion. (2) In the second stage, the time of inflow sap from noon to night is significantly shortened, while the outflow sap from fruit is observed with the enhancement of leaf transpiration after sunrise, which is consistent with the slow fruit growth at this stage. (3) In the third stage, the sap flow maintains the diurnal pattern. However, the sap flow that inputs the fruit at night is basically equal to the sap flow that outputs the fruit during the day; the fruit phenotype does not change anymore. In addition, a strong correlation between the daily mass growth in fruit and the daily sap flow amount in fruit stalk was identified, validating the sensor’s utility for fruit growth monitoring and yield prediction.

Objective To solve the difficulty of RhD blood group typing in a patient with double population(DP) of red blood cells for RhD antigen by serological and genotyping analysis. Methods Separation of the two populations of red blood cells of the patient was performed using capillary centrifugation method. ABO, RhD and RhCE typing, direct anti-human globulin test (DAT), irregular antibody screening, antibody identification and blood crossmatching of the patient were conducted using the standard serological methods. The hybrid Rhesus zygosity analysis of the RHD gene was performed by PCR-RFLP method. RHD and RHCE genotype of the patients were identified by PCR-SSP method. Results The patient was B type but with DP of red blood cells for RhD, Rhc and RhE antigens. DAT of the patient was positive and the alloanti-D was detected in serum. The RHD zygosity was D-/D- homozygote. PCR-SSP testing showed the RHD gene deletion (RHD * 01N. 01/01N.01 genotype) and Ccee of RHCE genotype in the patient, which was consistent with RHD zygosity analysis. Conclusion This is a special case with D-negative phenotype which was wrongly detected as D-positive type after D-positive red blood cells transfusion in emergency. When the DP of red cells for D antigen encountered like this case, the RhD typing can be accurately determined by using RHD genotyping analysis to provide strong evidence to the clinical blood transfusion.

Drought, an intricate natural phenomenon globally, significantly influences the gross primary productivity (GPP) and carbon sink potential of tropical forests. Present research on the drought response primarily focuses on natural forests, such as the Amazon rainforest, with relatively limited studies on tropical plantations. Therefore, for a comprehensive understanding of global climate change, accurately evaluating and analyzing the sensitivity and vulnerability of rubber plantation GPP to various drought characteristics is crucial. The Standardized Precipitation Evapotranspiration Index (SPEI) was used in this research to quantify drought intensity. The Spatially Explicit Individual Based Dynamic Global Vegetation Model (SEIB-DGVM) was localized based on observation data from the Hainan Danzhou Tropical Agro-ecosystem National Observation and Research Station. Subsequently, the calibrated model was utilized to simulate the dynamic process of rubber plantation GPP under multi-gradient drought scenarios (2 extreme boundaries × 3 drought initiation seasons × 4 drought intensities × 12 drought durations × 12 SPEI time scales). The results show that the sensitivity and vulnerability of rubber plantation GPP exhibit significant differences under drought scenarios in different initiation seasons; GPP exhibits higher sensitivity to extreme, long-duration flash droughts in the early rainy season. Regarding vulnerability, the impact of extreme, long-duration flash droughts on GPP is most pronounced. This research lays the foundation for estimating the impact of droughts on the GPP of rubber plantations under future climate change scenarios, providing a scientific basis for enhancing regional ecological restoration and protection.

Dwarf apple is one of the most important forms of garden economy, which has become a new engine for rural revitalization. The effective detection of coloring and ripening apples in complex environments is important for the sustainable development of smart agricultural operations. Addressing the issues of low detection efficiency in the greenhouse and the challenges associated with deploying complex target detection algorithms on low-cost equipment, we propose an enhanced lightweight model rooted in YOLOv7. Firstly, we enhance the model training performance by incorporating the Squeeze-and-Excite attention mechanism, which can enhance feature extraction capability. Then, an SCYLLA-IoU (SIoU) loss function is introduced to improve the ability of extracting occluded objects in complex environments. Finally, the model was simplified by introducing depthwise separable convolution and adding a ghost module after up-sampling layers. The improved YOLOv7 model has the highest AP value, which is 10.00%, 5.61%, and 6.00% higher compared to YOLOv5, YOLOv7, and YOLOX, respectively. The improved YOLOv7 model has an MAP value of 95.65%, which provides higher apple detection accuracy compared to other detection models and is suitable for potted dwarf anvil apple identification and detection.

Objective To establish a high-throughput detection method for ABCG2*376T allele of Jr(a-), and apply it to the study of the frequency of this allele in the Chinese population. Methods The specific primers were designed and synthesized, the sample carrying homozygous ABCG2*376T alleles, obtained in the previous study, was used as the homozygous positive control, and the sample carrying heterozygous allele as the heterozygous positive control. The wild-type sample was used as a negative control, and a high-resolution melting curve(HRM) method for detecting this allele was established. The established method was used to screen DNA samples from blood donors in Guangzhou, and the samples carrying ABCG2*376T alleles were sequenced to confirm the accuracy of the HRM method. Results A HRM method, which can detect ABCG2*376T allele and accurately type homozygotes and heterozygotes at the same time, had been established successfully. Fifteen individuals with heterozygous alleles were screened out of 1 560 blood donors in Guangzhou, while none homozygous allele was detected. Conclusion The HRM method can be used to accurately screen and type ABCG2*376T allele. The frequency of this allele in Chinese population is about 0.48%(15/3120).

Abstract Visual tracking is an important area in computer vision. Based on the Siamese network, current tracking methods employ the self‐attention block in convolutional networks to extract semantic features containing the image structure information of an object. However, spatial continuity is a point of contradiction between two seemingly unrelated challenges, that is, occlusion and similar distractor, in tracking methods. At the same time, it is a spatially discontinuous task to locate a target reappearing after occlusion accurately. The prediction of bounding boxes should be constrained by spatial continuity to prevent them from jumping into similar distractors. This study proposes a novel tracking method for introducing spatial continuity in visual tracking called M‐CoTransT; the novel tracking method is developed through the confidence‐based adaptive Markov motion model (M‐model) and a novel correlation‐based feature fusion network (CoTransT). In particular, the M‐model provides confidence for the nodes of the Markov motion model to estimate the motion state continuity. It also predicts a more accurate search region for CoTransT, which then adds a cross‐correlation branch into the self‐attention tracking network to enhance the continuity of target appearance in the feature space. Extensive experiments on five challenging datasets (LaSOT, GOT‐10k, TrackingNet, OTB‐2015 and UAV123) demonstrated the effectiveness of the proposed M‐CoTransT in visual tracking.

Topological phase transition materials have strong coupling between their charge, spin orbitals, and lattice structure, which makes them have good electrical and magnetic properties, leading to promising applications in the fields of memristive devices. The smaller Gibbs free energy difference between the topological phases, the stable oxygen vacancy ordered structure, and the reversible topological phase transition promote the memristive effect, which is more conducive to its application in information storage, information processing, information calculation, and other related fields. In particular, extracting the current resistance or conductance of the two-terminal memristor to convert to the weight of the synapse in the neural network can simulate the behavior of biological synapses in their structure and function. In addition, in order to improve the performance of memristors and better apply them to neuromorphic computing, methods such as ion doping, electrode selection, interface modulation, and preparation process control have been demonstrated in memristors based on topological phase transition materials. At present, it is considered an effective method to obtain a unique resistive switching behavior by improving the process of preparing functional layers, regulating the crystal phase of topological phase transition materials, and constructing interface barrier-dependent devices. In this review, we systematically expound the resistance switching mechanism, resistance switching performance regulation, and neuromorphic computing of topological phase transition memristors, and provide some suggestions for the challenges faced by the development of the next generation of non-volatile memory and brain-like neuromorphic devices based on topological phase transition materials.

Objective To identify the antibody specificity in a pregnant women who had no history of blood transfusion but presented the antibodies against high-frequency antigens. Methods ABO, RhD blood group antigens were identified by saline. Antibody screening and identification were performed by saline and indirect Coomb’s technique. Further antibody identification tests were conducted using papain, trypsin and chymotrypsin-treated cells. Antibody titer in serum was tested. PCR amplification and sequencing analysis of 16 exons of ABCG2 gene were conducted. Results The blood type of the patient were B, RhD positive. The serum reacted with antibody screening/identified cells by indirect antiglobin test(both 2+ ) but not by saline. The agglutination was enhanced after papain treatment (4+ ), but remained unchanged after trypsin and chymotrypsin treatment (2+ ). The IgG titer was 1∶2. The sequencing analysis of ABCG2 gene revealed a homozygous nonsense mutation(c.376C>T, p. Gln126X) in exon 4 of the women. Conclusion In this case, the development of anti-Jra in Jr(a-) mother was stimulated by mother-child serology incompatibility during pregnancy.

In response to water deficiency in Northern China, a scheme called the Middle Route Project was devised under the South-to-North Water Transfer Division to divert water from the Han River, the biggest tributary of the Yangtze River, to supply two provinces (Henan and Hebei) and two municipalities (Beijing and Tianjin) in the north. The minimum water qualityindex (WQImin) based on four water quality parameters and Mann-Kendall test methods were applied to determine the status of overall water quality inDanjiangkou reservoir (DKR) and downstream of Han River before and after the water intake (from 2006 to 2018). Results show that pH, dissolved oxygen, chemical oxygen demand, and ammonia nitrogen of water showed similar seasonal trends at the reservoir center, intaking place and downstream of Han River. According to WQImin index, the water quality status of most water samples at reservoir and downstream remained at good. After water diversion, water quality did not significantly differ from the status before intake at reservoir center. However, water quality was improved at intaking place and downstream. Inter-basin water diversion from reservoir did not deteriorate the local and downstream water quality, or significantly reduce the downstream flow discharge before it pours into Yangtze River. This study can inform other regions with serious water crises that both water diversion and local water quality can be preserved with appropriate environmental managements.