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Diffractions are seismic waves generated by small-scale heterogeneities in the subsurface. These are often superimposed by strong reflections so that they are not visible on the image, leading to misinterpretation and incorrect localization of the scatterers. Therefore, the separation of diffracted and reflected waves is a crucial step in identifying these small-scale diffractors. To realize the separation of diffraction and imaging, a least-squares reverse time migration method of plane waves (PLSRTM) optimized with short-time singular spectrum analysis (STSSA) was developed in this work. The proposed STSSA algorithm exploits the properties of singular spectral analysis (SSA) to separate linear signals. By establishing the Hanning window and the energy compensation function, it also compensates for the shortcomings of SSA in local dip processing and convergence of linear signals. As there is no clear boundary between reflected and diffracted waves, the energy loss during separation leads to a slow convergence rate of the diffraction wave imaging technique. We use STSSA as a constraint for PLSRTM, which greatly improves the imaging quality for diffraction waves. The tests with the Sigsbee2A model and noisy seismic data have shown that our method can effectively improve the resolution of diffraction wave imaging and that the constraint of STSSA increases the robustness to noisy data.

The post-1980 regional climate change increased dust AOD by +12.5 ± 15.0% and +43.6 ± 31.2% over the source and downstream areas respectively during a record-breaking dust storm in March 2021 in North China.

Anisotropy of subsurface media can affect the seismic wave travel time estimates, and then affect the imaging of target regions. To calibrate the effect of anisotropy, a VTI (transverse isotropy media with vertical symmetry axis) least-squares reverse-time migration (LSRTM) algorithm is used. However, if seismic data contains noise especially the outliers, the high-quality images cannot be produced by LSRTM based on an L2 norm. Considering that Student's t-distribution has better robustness than the L2 norm, this study derives a VTI-LSRTM algorithm based on Student's t-distribution (T-VTI-LSRTM) misfit function. The plane-wave encoding is introduced into the T-VTI-LSRTM to improve the computational efficiency. We conduct numerical tests using the complex models to illustrate the effectiveness and adaptability of the method. The sensitivity analysis of velocity and anisotropy parameters demonstrate that anisotropy and velocity parameters have a distinct effect on imaging results, in which velocity sensitivity is the strongest, then the epsilon and parameter delta sensitivity is the weakest.

The unique characteristics of land–air coupling and troposphere–stratosphere interaction over the Tibetan Plateau (TP), the highest landform in the world, play a vital role in weather and climate on regional and global scales. Although a great deal of research has been carried out, large gaps remain in our understanding of TP land–air coupling and its climate effects, due to a lack of observations and the issue of model biases. To address these obstacles, a 10-yr national research program entitled “Changes in the Land–Air Coupled System over the Tibetan Plateau and its Impacts on Global Climate (LASTPIC)” was launched by the National Natural Science Foundation of China in January 2014. What LASTPIC does revolves around three aspects: TP land–air coupled processes; TP’s influence on global climate; and reanalysis and model. This paper mainly focuses on the data collection, scientific understanding, and model development of LASTPIC in terms of TP land–atmosphere–ocean coupling and its global climate impacts since program’s inception.

Predicting climate anomalies months in advance is of tremendous socioeconomic value. Facing both theoretical and practical constraints, this realm of "seasonal prediction" progressed slowly in recent decades. Here we devise an innovative scheme that pushes the boundary of seasonal prediction by recognizing and isolating distinct spatiotemporal footprints left by modes of climate variability that cause varying annual cycles in response to the solar forcing. The predictive power harnessed from these spatiotemporal footprints results in a prediction skill surpassing existing models for seasonal forecasts of eastern China rainfall, which is one of the most challenging seasonal prediction problems. By considering varying annual cycles explicitly, the new scheme is able to predict multi-provincial flood and/or drought occurrences seamlessly over an entire year. This novel scheme is generically applicable for improving seasonal forecasts over other monsoon regions and for critical climate variables such as surface temperature and Arctic sea-ice extent.

In exploration seismology, reflections have been extensively used for imaging and inversion to detect hydrocarbon and mine resources, which are generated from subsurface continuous impedance interfaces. When the interface is not continuous and its size reduces to less than half-wavelength, reflected wave becomes diffraction. Reflections and diffractions can be used to image subsurface targets, and the latter is helpful to resolve small-scale discontinuities, such as fault plane, pinch out, Karst caves, and salt edge. However, the amplitudes of diffractions are usually much weaker than that of reflections. This makes it difficult to directly identify and extract diffractions from unmigrated common-shot or common-middle-point gathers. Migrating seismic data into a subsurface location for different reflector dip angles yields a dip-angle-domain common-image gather (DACIG). One DACIG represents the migrated traces at a fixed lateral position for different reflector dips. The reflection and diffraction have different geometric characteristics in DACIG, which provides one opportunity to separate diffractions and reflections. In this study, we present an efficient and accurate diffraction separation and imaging method using a convolutional neural network (CNN). The training data set of DACIGs is generated using one pass of seismic modeling and migration for velocity models with and without artificial scatterers, respectively. Then, a simplified end-to-end CNN is trained to identify and extract reflections from the migrated DACIGs that contain reflections and diffractions. Next, two adaptive subtraction strategies are presented to compute the diffraction DACIGs and stacked images, respectively. Numerical experiments for synthetic and field data demonstrate that the proposed method can produce accurate reflection and diffraction separation results in DACIGs, and the stacked image has a good resolution for subsurface small-scale discontinuities.

In the elastic medium, the scalar and vector P- and S-waves decomposition has been extensively studied and some strategies can be extended to the poroelastic medium to extract P- and S-wavefields. However, there are three propagation modes in the poroelastic medium in Biot’s theory, namely, a fast P wave, a slow P wave, and an S wave. Because the propagation characteristic of a slow P wave is different from that of a fast P wave and S wave, the wavefield separation methods in the elastic medium cannot be directly applied to the poroelastic medium to produce a complete wave-mode separation. Based on the eigenform analysis, we have developed a hierarchical wavefield decomposition method to completely separate S waves and fast and slow P waves in the poroelastic medium. Using the Helmholtz decomposition, we first compute scalar and vector potential wavefields to separate P and S waves. Then, a cross-product operator is proposed to decompose fast and slow P waves based on their different polarization directions. To produce correct amplitudes and phases, we apply another cross-product operator and an amplitude correction term to the separated wavefields. Three numerical examples demonstrate that our method can produce accurate fast P-wave, slow P-wave, and S-wave separation results, and the decomposed fast and slow P waves have the same phases and amplitudes as the P-wave potential wavefields.

Plant sap flow is crucial to understanding plant transpiration, plant hydraulic functioning and physiological properties. In this study, a method for predicting trunk sap flow of Larix olgensisusing deep learning was proposed. The method is based on the combined use of Long-short term memory network (LSTM) and transformer model, noted as LSTM-transformer model. The experimental results show that the proposed method provides more accurate prediction quality in terms of correlation coefficient (R2), root mean square error (RMSE) and mean absolute error (MAE), compared to the state of the art forecast methods such as BP, DNN, LSTM, and transformer models.

Critical-sized cranial bone defect remains a great clinical challenge. With advantages in regenerative medicine, injectable hydrogels incorporated with bioactive molecules show great potential in promoting cranial bone repair. Recently, we developed a dual delivery system by sequential release of bone morphogenetic protein 2 (BMP2) followed by insulin-like growth factor 1 (IGF1) in microparticles (MPs), and an injectable alginate/collagen (alg/col)-based hydrogel. In this study, we aim to evaluate the effect of dual delivery of BMP2 and IGF1 in MPs through the injectable hydrogel in critical-sized cranial bone defect healing. The gelatin MPs loaded with BMP2 and poly(lactic-co-glycolic acid)-poly(ethylene glycol)-carboxyl (PLGA-PEG-COOH) MPs loaded with IGF1 were prepared, respectively. The encapsulation efficiency and release profile of growth factors in MPs were measured. A cranial defect model was applied to evaluate the efficacy of the dual delivery system in bone regeneration. Adult Sprague Dawley rats were subjected to osteotomy to make an ⌀8-mm cranial defect. The injectable hydrogel containing MPs loaded with BMP2 (2 μg), IGF1 (2 μg), or a combination of BMP2 (1 μg) and IGF1 (1 μg) were injected to the defect site. New bone formation was evaluated by microcomputed tomography, histological analysis, and immunohistochemistry after 4 or 8 weeks. Data showed that dual delivery of the low-dose BMP2 and IGF1 in MPs through alg/col-based hydrogel successfully restored cranial bone as early as 4 weeks after implantation, whose effect was comparable to the single delivery of high-dose BMP2 in MPs. In conclusion, this study suggests that dual delivery of BMP2 and IGF1 in MPs in alg/col-based hydrogel achieves early bone regeneration in critical-sized bone defect, with advantage in reducing the dose of BMP2. Impact Statement Sequential release of bone morphogenetic protein 2 (BMP2) followed by insulin-like growth factor 1 (IGF1) in two different microparticles promotes critical-sized bone defect healing. This dual delivery system reduces the dose of BMP2 by supplementing IGF1, which may diminish the potential side effects of BMP2.

One of the most important and continuously growing research areas in marine ecology is assessing the sustainability of ecosystems. The concept is traditionally approached by quantifying different anthropogenic pressures, such as top-down effects, overexploitation, invasive species, overfishing, and pollution. However, this perspective has been criticized for its inability to capture the complex interactions between natural factors (such as climate change), human factors, and sociopolitical factors that shape ecosystems. In this paper, we present a new structural model for assessing the sustainability of marine ecosystems, PCA-DEA-based model, as an extension to current models that incorporates these key interfaces into dynamic system modeling by including trade-offs on horizontal scales (e.g., decision making).

Aim. Printing parameters have been studied extensively to improve printing performance, while resins have been studied to a lesser extent. Therefore, we explore the impact of value in the Munsell color system on the mechanical properties and accuracy of printed products. Materials and Methods. Resins having different values were prepared by mixing transparent resin and color pastes. We used plate models for mechanical measurement, crown-and bridge models for accuracy measurement, and disc models for color measurement. Results. The Group E resin, which had the lowest value, had the minimum ultimate flexural strength (61.199 MPa) and a relatively low elastic modulus (19.015 MPa). Excluding the d index, no significant difference in accuracy was observed. In terms of the d index of trueness, the result of the Group E resin was significantly low. The relative errors of trueness were less than 0.0727 μm. The relative errors of precision were less than 0.0093 μm. Conclusion. The value of a resin affects the mechanical properties and accuracy of printed products. It is better to secure flexural strength by using a lower-value resin. High-value resins have relatively low accuracies.

The pseudoviscoacoustic anisotropic wave equation is widely used in the oil and gas industry for modeling wavefields in attenuating anisotropic media. Compared to the full viscoelastic anisotropic wave equation, it can greatly reduce the computational cost of wavefield modeling while maintaining the visco-qP-wave kinematics very well. However, even if we place the source in a thin isotropic layer, there will be some unwanted S-wave artifacts in the qP wavefield simulated by the pseudoviscoacoustic anisotropic wave equation due to the stepped approximation of inclined layer interfaces. Furthermore, the wavefield simulated by the pseudoviscoacoustic anisotropic wave equation may suffer from numerical instabilities when the anisotropy parameter epsilon is less than delta. To overcome these problems, we derive a pure-viscoacoustic tilted transversely isotropic (TTI) wave equation in media with anisotropy in velocity and attenuation based on the exact complex-valued phase velocity formula. The pure-viscoacoustic TTI wave equation has decoupled amplitude dissipation and phase dispersion terms, which is suitable for further reverse time migration with Q compensation. For numerical simulations, we adopt the second-order Taylor series expansion to replace the mixed-domain spatially variable fractional Laplacian operator, which guarantees the decoupling of the wavenumber from the space-related fractional order. Then, we use an efficient and stable hybrid finite-difference and pseudospectral method (HFDPSM) to solve the pure-viscoacoustic TTI wave equation. Numerical tests indicate that the simulation results of the newly derived pure-viscoacoustic TTI wave equation are stable, free from S-wave artifacts, and accurate. We further demonstrate that HFDPSM outperforms the pseudospectral method in terms of numerical simulation stability and computing efficiency.

A new dynamical core, known as the Finite-Volume Cubed-Sphere (FV3) and developed at both NASA and NOAA, is used in NOAA's Global Forecast System (GFS) and in limited-area models for regional weather and air quality applications. NOAA has also upgraded the operational FV3GFS to version 16 (GFSv16), which includes a number of significant developmental advances to the model configuration, data assimilation, and underlying model physics, particularly for atmospheric composition to weather feedback. Concurrent with the GFSv16 upgrade, we couple the GFSv16 with the Community Multiscale Air Quality (CMAQ) model to form an advanced version of the National Air Quality Forecasting Capability (NAQFC) that will continue to protect human and ecosystem health in the US. Here we describe the development of the FV3GFSv16 coupling with a “state-of-the-science” CMAQ model version 5.3.1. The GFS–CMAQ coupling is made possible by the seminal version of the NOAA-EPA Atmosphere–Chemistry Coupler (NACC), which became a major piece of the next operational NAQFC system (i.e., NACC-CMAQ) on 20 July 2021. NACC-CMAQ has a number of scientific advancements that include satellite-based data acquisition technology to improve land cover and soil characteristics and inline wildfire smoke and dust predictions that are vital to predictions of fine particulate matter (PM2.5) concentrations during hazardous events affecting society, ecosystems, and human health. The GFS-driven NACC-CMAQ model has significantly different meteorological and chemical predictions compared to the previous operational NAQFC, where evaluation of NACC-CMAQ shows generally improved near-surface ozone and PM2.5 predictions and diurnal patterns, both of which are extended to a 72 h (3 d) forecast with this system.

Central Asia (CA; 35°–55°N, 55°–90°E) has been experiencing a significant warming trend during the past five decades, which has been accompanied by intensified local hydrological changes. Accurate identification of variations in hydroclimatic conditions and understanding the driving mechanisms are of great importance for water resource management. Here, we attempted to quantify dry/wet variations by using precipitation minus evapotranspiration (P − E) and attributed the variations based on the atmosphere and surface water balances. Our results indicated that the dry season became drier while the wet season became wetter in CA for 1982–2019. The land surface water budget revealed precipitation (96.84%) and vapor pressure deficit (2.26%) as the primary contributing factors for the wet season. For the dry season, precipitation (95.43%), net radiation (3.51%), and vapor pressure deficit (−2.64%) were dominant factors. From the perspective of the atmospheric water budget, net inflow moisture flux was enhanced by a rate of 72.85 kg m−1 s−1 in the wet season, which was mainly transported from midwestern Eurasia. The increase in precipitation induced by the external cycle was 11.93 mm (6 months)−1. In contrast, the drying trend during the dry season was measured by a decrease in the net inflow moisture flux (74.41 kg m−1 s−1) and reduced external moisture from midwestern Eurasia. An increase in precipitation during the dry season can be attributed to an enhancement in local evapotranspiration, accompanied by a 4.69% increase in the recycling ratio. The compounding enhancements between wet and dry seasons ultimately contribute to an increasing frequency of both droughts and floods.

The long-term ozone changes in the middle to upper troposphere, of importance to climate radiative forcing and setting the baseline for tropospheric ozone pollution, are not well quantified from observations in East Asia. In this study, three decades of observations from ozone soundings are examined with meteorological reanalysis data and climate model simulations to characterize regional features in tropospheric ozone and investigate their driving factors along the northwestern Pacific coastal region. A rapid increase in ozone is observed in the middle to upper troposphere over Naha (26 oN), Tsukuba (36 oN), and Sapporo (43 oN) in the warm season during 1990‒2020. Coincidentally, tongue-shaped hotspots with high tropospheric ozone extending from the stratosphere occur during the warm season. The timing for these ozone hotspots shows a time lag from late spring to summer with the increasing latitude of the observation sites. Intensified stratospheric intrusion (i.e., tropopause folding) events and enhanced buildup of ozone abundance in the lowermost stratosphere (likely driven by climate change) are the key factors causing the large increase over this region. With the aid of the chemistry climate model EMAC, the enhanced downward transport of stratospheric ozone into the troposphere is revealed by a surge in the stratospheric ozone tracer in the troposphere.

The oceanic meridional overturning circulation (MOC) is a key player in the global climate system, while continental topography provides an essential backdrop to the Earth's climate. In this study, we investigate the influence of various mountain ranges on the global thermohaline circulation through a series of coupled model experiments. Our findings reveal that the Tibetan Plateau (TP) exerts the most significant impact on the global thermohaline circulation, serving as a necessary condition for the establishment of the Atlantic MOC (AMOC) and a sufficient condition for the collapse of the Pacific MOC (PMOC). Additionally, the Antarctic continent plays a vital role in facilitating the TP to form the AMOC. Although no individual mountain range can give rise to the AMOC independently, the TP alone can suppress the development of the PMOC. Through altering the global hydrological cycle, the TP may have played a pivotal role in shaping the global thermohaline circulation.

Licorice, a traditional Chinese medicine, has been widely used for the treatment of COVID-19, but all active compounds and corresponding targets are still not clear. Therefore, this study proposed a deep learning-based network pharmacology approach to identify more potential active compounds and targets of licorice. 4 compounds (quercetin, naringenin, liquiritigenin, and licoisoflavanone), 2 targets (SYK and JAK2) and the relevant pathways (P53, cAMP, and NF-kB) were predicted, which were confirmed by previous studies to be associated with SARS-CoV-2-infection. In addition, 2 new active compounds (glabrone and vestitol) and 2 new targets (PTEN and MAP3K8) were further validated by molecular docking and molecular dynamics simulations (simultaneous molecular dynamics), as well as the results showed that these active compounds bound well to COVID-19 related targets, including the main protease (Mpro), the spike protein (S-protein) and the angiotensin-converting enzyme 2 (ACE2). Overall, in this study, glabrone and vestitol from licorice were found to inhibit viral replication by inhibiting the activation of Mpro, S-protein and ACE2; related compounds in licorice may reduce the inflammatory response and inhibit apoptosis by acting on PTEN and MAP3K8. Therefore, licorice has been proposed as an effective candidate for the treatment of COVID-19 through PTEN, MAP3K8, Mpro, S-protein and ACE2.

Long-term or supra-physiological dose of glucocorticoid (GC) application in clinic can lead to impaired bone growth and osteoporosis. The side effects of GC on the skeletal system are particularly serious in growing children, potentially causing growth retardation or even osteoporotic fractures. Children’s bone growth is dependent on endochondral ossification of growth plate chondrocytes, and excessive GC can hinder the development of growth plate and longitudinal bone growth. Despite the availability of drugs for treating osteoporosis, they have failed to effectively prevent or treat longitudinal bone growth and development disorders caused by GCs. As of now, there is no specific drug to mitigate these severe side effects. Traditional Chinese Medicine shows potential as an alternative to the current treatments by eliminating the side effects of GC. In summary, this article comprehensively reviews the research frontiers concerning growth and development disorders resulting from supra-physiological levels of GC and discusses the future research and treatment directions for optimizing steroid therapy. This article may also provide theoretical and experimental insight into the research and development of novel drugs to prevent GC-related side effects.

Confirmation of calculation strategy of evaluating immune infiltration between two MB subtypes via staining of different APC markers. Same differential expression in Ptch1 tumor model observed.

Supplementary Table 1:Tumors maintained expression of subgroup genes previously identified as unique to corresponding human MB subtypes, SHH and Group 3 tumors, respectively. Supplementary Table 2: Flow cytometric antibody panel.

Orthotopically transplanted tumors are uniformly lethal at determined minimum tumorigenic dose. (A) Tumors arising from Patched1 heterozygous (Ptch1+/-) mice and immune deficient NOD scid gamma (NSG) mice implanted with retrovirally transduced cerebellar neural stem cells (NSC) were serially passaged via stereotactic implantation in the cerebellum of immunocompetent C57BL/6 hosts. Animals were implanted with varying numbers of tumor cells to determine the minimum dose required to induce 100% lethality in tumor-bearing mice within one month. Stereotactic implantation of (B) 1 x 103 NSC MB tumor cells and (C) 1.25 x 105 Ptch1 MB cells were determined as the minimum tumorigenic dose carried forth in subsequent animal studies.

Gating strategy for NSC MB Tumors.

Gating strategy for Ptch1 MB tumors.

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