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Quinazolines and their derivatives occur in various natural products and pharmaceuticals, and thus, various methods of synthesizing quinazolines have been explored. They have traditionally been synthesized via two‐component reactions, but these strategies often suffer from the unavailability of the starting materials and limited substrate scopes. To overcome these problems, three‐component reactions using additional N sources were developed. Aldehydes were initially used in these reactions, but alcohols are greener and less toxic than aldehydes. However, the previously reported methods involving the use of alcohols require the utilization of transition metal catalysts, ultrahigh temperatures, and extended durations. Thus, an efficient, practical method of synthesizing quinazolines using alcohol is desirable. A facile one‐pot three‐component method of synthesizing quinazolines utilizing alcohols, 2‐aminobenzoketones, and ammonium acetate is reported for the first time, using active MnO2 and tert‐butyl hydrogen peroxide (TBHP) as synergistic oxidants. MnO2 and TBHP play dual roles: First, they oxidize the alcohol to the aldehyde and then facilitate the transformation of the intermediate into the product. During alcohol oxidation, the synergistic effect of MnO2 and TBHP is particularly evident. The aldehydes generated in situ via alcohol oxidation undergo immediate subsequent reactions, thereby minimizing their volatilization and side reactions, such as oxidation and polymerization. [ABSTRACT FROM AUTHOR]

The widespread and complex formation of saline soils in China significantly affects the sustainable development of regional ecosystems. Intense climate changes and regional land use further exacerbate the uncertainties faced by ecosystems in saline areas. Therefore, studying the distribution characteristics of typical halophytic vegetation under the influence of climate change and human activities, and exploring their potential distribution areas, is crucial for maintaining ecological security in saline regions. This study focuses on Tamarix chinensis, Tamarix austromongolica, and Tamarix leptostachya, integrating geographic information systems, remote sensing, species distribution models, and landscape ecological risk (LER) theories and technologies. An optimized MaxEnt model was established using the ENMeval package, incorporating 143, 173, and 213 distribution records and 13 selected environmental variables to simulate the potential suitable habitats of these three Tamarix species. A quantitative assessment of the spatial characteristics and the area of their potential geographical distribution was conducted. Additionally, a landscape ecological risk assessment (LERA) of the highly suitable habitats of these three Tamarix species was performed using land use data from 1980 to 2020, and the results of the LERA were quantified using the Landscape Risk Index (LERI). The results showed that the suitable areas of Tamarix chinensis, Tamarix austromongolica, and Tamarix leptostachya were 9.09 × 105 km2, 6.03 × 105 km2, and 5.20 × 105 km2, respectively, and that the highly suitable habitats for the three species were concentrated in flat areas such as plains and basins. Tamarix austromongolica faced increasing ecological risk in 27.22% of its highly suitable habitat, concentrated in the northern region, followed by Tamarix chinensis in 16.70% of its area with increasing ecological risk, concentrated in the western and northern highly suitable habitats; Tamarix chinensis was the least affected, with an increase in ecological risk in only 1.38% of its area. This study provides valuable insights for the protection of halophytic vegetation, represented by Tamarix, in the context of China's national land development. [ABSTRACT FROM AUTHOR]

The movement of glaciers plays a crucial role in environmental and geological processes, significantly influencing the formation and dynamics of ice bodies. This study leverages feature tracking technology to analyze optical and Synthetic Aperture Radar (SAR) remote sensing imagery, specifically GF-1 optical images and GF-3, Sentinel-1 SAR images, captured during the 2020 to 2021 ablation season in Gongar. The aim was to quantify glacier surface velocities and to evaluate the comparative effectiveness of different remote sensing modalities in capturing these dynamics. Our findings indicate a strong consistency in the spatial distribution of glacier surface velocities derived from diverse remote sensing data sources, with high-precision optical imagery (GF-1) yielding the most accurate velocity measurements, followed by Sentinel-1 SAR data. Notably, large glaciers in Gongar exhibited rapid movements, with an average velocity of 0.16 m/d, primarily at elevations between 4,500 and 6,500 m. The fastest velocities were recorded at approximately 4,500 m elevation. Glaciers with inclines ranging from 10° to 60° displayed the highest velocities within the 20°-30° slope range. It was observed that glaciers on the southeast slope moved faster, exhibiting the highest average surface velocity, in contrast to those on the west slope, which moved more slowly. The surface velocity of the ice tongue region of Krayaylak Glacier that the largest glacier in Pamir, was observed to be lower than 0.6 m/d, indicating a slow movement speed. The study also reveals that the effectiveness of different remote sensing data in detecting glacier velocity in Gongar, with high-resolution data more accurately capturing surface velocities in melting areas or those with slower movement. This study underscores the importance of multi-source remote sensing data in understanding glacier dynamics and contributes valuable insights into the mechanisms driving glacier movements. [ABSTRACT FROM AUTHOR]

With its unique properties and potential applications, nanoparticle-based delivery platforms for messenger RNA (mRNA) vaccines have gained significant attention in recent years. Nanoparticles have the advantages of enhancing immunogenicity, targeting delivery, and improving stability, providing a new solution for drug and vaccine delivery. In some clinical studies, a variety of nanoparticle delivery platforms have been gradually applied to a wide range of vaccine applications. Current research priorities are exploring various types of nanoparticles as vaccine delivery systems to enhance vaccine stability and immunogenicity. Lipid nanoparticles (LNPs) have shown promising potential in preclinical and clinical studies on the efficient delivery of antigens to immune cells. Moreover, lipid nanoparticles and other nanoparticles for nucleic acids, especially for mRNA delivery systems, have shown vast potential for vaccine development. In this review, we present various vaccine platforms with an emphasis on nanoparticles as mRNA vaccine delivery vehicles. We describe several novel nanoparticle delivery platforms for mRNA vaccines, such as lipid-, polymer-, and protein-based nanoparticles. In addition, we provide an overview of the anti-tumor immunity of nanovaccines against different tumors in cancer immunotherapy. Finally, we outline future perspectives and remaining challenges for this promising technology of nanoparticle-based delivery platforms for vaccines. [ABSTRACT FROM AUTHOR]

The scattered seismic waves of fractured porous rock are strongly affected by the wave-induced fluid pressure diffusion effects between the compliant fractures and the stiffer embedding background. To include these poroelastic effects in seismic modeling, we develop a numerical scheme for discretely distributed large-scale fractures embedded in fluid-saturated porous rock. Using Coates and Schoenberg's local-effective-medium theory and Barbosa's dynamic linear slip model characterized by complex-valued and frequency-dependent fracture compliances, we derive the effective viscoelastic compliances in each spatial discretized cell by superimposing the compliances of the background and the fractures. The effective governing equations for fractured porous rocks are viscoelastic anisotropic and numerically solved by the mixed-grid-stencil frequency-domain finite-difference method. The main advantage of our proposed modeling scheme over poroelastic modeling schemes is that the fractured domain can be modeled using a viscoelastic solid, while the rest of the domain can be modeled using an elastic solid. We have tested the modeling scheme in a single fracture model, a fractured model, and a modified Marmousi model. The good consistency between the scattered waves off a single horizontal fracture calculated using our proposed scheme and the poroelastic modeling validates that our modeling scheme can properly capture the fluid pressure diffusion (FPD) effects. In the case of a set of aligned fractures, the scattered waves from the top and bottom of the fractured reservoir are strongly influenced by the FPD effects, and the reflected waves from the underlying formation can retain the relevant attenuation and dispersion information. The proposed numerical modeling scheme can also be used to improve migration quality and the estimation of fracture mechanical characteristics in inversion. [ABSTRACT FROM AUTHOR]

As transport channels of oil and gas, fracture networks can greatly improve reservoir seepage, which is of great significance to the hydraulic fracturing and hydrocarbon deposit exploitation in petroleum science and engineering. In this paper, our target reservoirs are deep karsted carbonates at depths of >6000 m and highly heterogeneous, leading to complex seismic responses with weak energy and low resolution. Therefore, it is challenging to predict the spatial distribution of a carbonate fracture-cavern reservoir and to characterize its delicate structure. We present a characterization method for an excellent fracture description by integrating several attribute results on 3D seismic field data. First, we use a noise elimination method to remove the noise interference in seismic data without damaging the fault structure characteristics. Next, we propose a novel spatially windowed 2D Hilbert transform-based operator to perform volumetric edge detection on 3D seismic field data. Then, the volumetric edge results are co-rendered with other seismic geometric attributes to generate multi-attribute fusion results for a comprehensive prediction that can excellently delineate geologic anomalies at different scales in deep carbonates. The results indicate that integrating several scale attributes can obtain more rich geological discontinuity and reveal more subtle fractures than using single attribute. The multi-attribute fusion results can effectively delineate some small-medium-sized faults, and they provide practical support for the exploration and production of Tahe carbonate fracture-cavern reservoirs. [ABSTRACT FROM AUTHOR]

Coal mine rockburst is closely related to the complex geological structure. Understanding the criterion of the fault activation instability and the disaster-causing mechanism of rockburst under the influence of mining is the theoretical premise and important guarantee of safe and efficient coal mining. In this paper, based on the theory of key stratum, the mechanical model of fault slip instability in the normal fault during the hanging wall mining was established, and the instability criterion was derived. It is concluded that the fault slip instability of the hanging wall is mainly controlled by two factors: (1) the distance between coal seams and key stratum and (2) the distance between working face and fault. Moreover, these two factors have an inverse relation to the occurrence of rockburst. Subsequently, three conceptual models of rockburst induced by the fault stress transfer, stress concentration of coal pillars, and fault structural instability were proposed. Based on the rock mechanics theory, the rockburst carrier system model of “roof-coal seam-floor” near the fault was established. The mechanical essence of fault rockburst was obtained as follows: under the action of fault, the static load of fault coal pillar was increased and superimposed with the fault activation dynamic load, leading to high-strength rockburst disaster. Based on the occurrence mechanism of fault rockburst, the monitoring and prevention concept and technical measures were proposed in three aspects, including the monitoring and control of fault activation dynamic loads, the monitoring of high static load in fault coal pillar and stress release, and the strengthening roadway support. These prevention and control measures were verified in the panel 103down02 of the Baodian Coal Mine in engineering, and the effectiveness of these measures was proved.

To effectively monitor and control the severe mining-induced rockburst in deep fault area, the fault activation law and the mechanical essence of rockburst induced by crossing fault mining were studied through theoretical analysis, microseismic monitoring, field investigation, and other methods; numerical simulation was employed to verify the obtained fault activation law and the mechanical nature. First, the distribution of microseismic sources at different mining locations and the fault activation degree were analyzed. According to the microseismic frequency and the characteristics of the energy stage, the fault activation degree was divided into three stages: fault stress transfer, fault pillar stress behavior, and fault structure activation. It was determined that the impact disaster risk was the strongest in the stage of the fault pillar stress behavior. Based on the periodic appearance law of microseisms in fault area, three types of conceptual models of fault-type rockburst were proposed, and the rockburst carrier system model of “roof-coal seam-floor” in the fault area was established. The mechanical essence of fault-type rockburst was obtained as follows: under the action of fault structure, the static load of the fault coal pillar was increased and superimposed with the active dynamic load of the fault, leading to high-strength impact disaster. Finally, the prevention and treatment concepts of fault-type rockburst were proposed. The monitoring and prevention measures of fault-type rockburst were taken from two aspects: the monitoring and characterization of fault rockburst and weakening control of the high static load of the fault coal pillar and dynamic load of fault activation. The proposed concepts and technical measures have been verified in the working face 14310 of Dongtan Coal Mine with sound results. The research results have a guiding significance for the prevention and control of rockburst in a similar mining face under crossing fault mining.

Given its progressive deterioration in the clinical course, noninvasive assessment and risk stratification for the severity of renal fibrosis in chronic kidney disease (CKD) are required. We aimed to develop and validate an end-to-end multilayer perceptron (MLP) model for assessing renal fibrosis in CKD patients based on real-time two-dimensional shear wave elastography (2D-SWE) and clinical variables. From April 2019 to December 2021, a total of 162 patients with CKD who underwent a kidney biopsy and 2D-SWE examination were included in this single-center, cross-sectional, and prospective clinical study. 2D-SWE was performed to measure the right renal cortex stiffness, and the corresponding elastic values were recorded. Patients were categorized into two groups according to their histopathological results: mild and moderate-severe renal fibrosis. The patients were randomly divided into a training cohort (n = 114) or a test cohort (n = 48). The MLP classifier using a machine learning algorithm was used to construct a diagnostic model incorporating elastic values with clinical features. Discrimination, calibration, and clinical utility were used to appraise the performance of the established MLP model in the training and test sets, respectively. The developed MLP model demonstrated good calibration and discrimination in both the training [area under the receiver operating characteristic curve (AUC) = 0.93; 95% confidence interval (CI) = 0.88 to 0.98] and test cohorts [AUC = 0.86; 95% CI = 0.75 to 0.97]. A decision curve analysis and a clinical impact curve also showed that the MLP model had a positive clinical impact and relatively few negative effects. The proposed MLP model exhibited the satisfactory performance in identifying the individualized risk of moderate-severe renal fibrosis in patients with CKD, which is potentially helpful for clinical management and treatment decision-making. [ABSTRACT FROM AUTHOR]

Frequency-domain wave modelling can easily describe the visco-acoustic behaviour of wave propagation using frequency-dependent velocities. Conventional finite-difference (FD) modelling in the frequency domain is computationally prohibitive for solving the acoustic Helmholtz equation in complicated and large geological models. To reduce the computational cost of traditional FD Helmholtz solvers, we develop a multiscale FD frequency-domain method that uses multiscale basis functions to significantly reduce the dimension of system matrices associated with the Helmholtz equation. Due to the insufficient accuracy of the first-order multiscale basis functions in the case of strongly heterogeneous models, we introduce the multinode coarse-element scheme into the scalar Helmholtz equation, a scheme previously developed in the extended multiscale finite-element method for vector problems. This multinode scheme enables multiscale basis functions to capture accurate fine-scale medium property variations. We use one homogeneous model and two heterogeneous models to validate our multiscale method for accuracy and computational cost. Numerical results demonstrate that our new approach can significantly reduce the time and memory costs of acoustic wave modelling while maintaining accuracy, indicating the great potential of our multiscale method in large-scale modelling applications. [ABSTRACT FROM AUTHOR]