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This study finds that the observed decrease in winter–spring Tibetan Plateau snow depth since 2000 has played an important role in weakening the correlation between rapidly intensifying tropical cyclones over the western North Pacific and tropical Indian Ocean sea surface temperatures (SSTs). Tibetan Plateau snow depth modulates convective activity through changes in the South Asian high. Increased Tibetan Plateau snow depth promotes basinwide tropical Indian Ocean cooling in spring through a Gill-type response. In the following seasons, downward latent heat flux anomalies associated with a weaker monsoon circulation contributes to warm SST anomalies over the western tropical Indian Ocean, thus favoring a positive phase of the Indian Ocean dipole. This evolution of tropical Indian Ocean SSTs associated with anomalously high Tibetan Plateau snow depth potentially weakens the relationship between rapidly intensifying tropical cyclone frequency and spring tropical Indian Ocean SSTs. When the effect of Tibetan Plateau snow depth is removed via partial correlation analysis, we find a significant relationship between spring tropical Indian Ocean SSTs and rapidly intensifying tropical cyclones as well as corresponding large-scale environmental factors. The results of this study enhance understanding of changes in tropical cyclone intensity and have implications for seasonal forecasting of tropical cyclone intensity over the western North Pacific basin. This study also emphasizes the importance of Tibetan Plateau thermal forcing in atmosphere–ocean coupling.

A session-based recommendation system (SRS) tries to predict the next possible choice of anonymous users. In recent years, graph neural network (GNN) models have been successfully applied to SRSs and have achieved great success. Using GNN models in SRSs, each session graph is processed successively to obtain the embedding of the node (i.e, each action on an item), which is then imported into the prediction module to generate recommendation results. However, solely depending on the session graph to obtain the node embeddings is not sufficient because each session only involves a few items. Therefore, neighbor sessions have been used to extend the session graph to learn more informative node representations. In this paper, we introduce a S ession-based recommendation MO del based on N eighbor sessions with similar probabilistic int E ntions(SMONE). SMONE models the intentions behind sessions in a probabilistic way and retrieves the neighbor sessions with similar intentions. After the neighbor sessions are found, the target session and its neighbor sessions are modeled as a hypyergraph to learn the contextualized embeddings, which are combined with item embeddings through GNN to produce the final item recommendations. Experiments on real-world datasets prove the effectiveness and superiority of SMONE.

After mining, upward fractures develop from bottom to top, and they are key channel for groundwater and gas flow and also sand burst; therefore, it is important to study the development mechanism and criterion of upward fractures. Combining with physical simulation and theoretical analysis, the development law of mining-induced upward fractures was revealed, and the mechanism and criterion of fracture propagation was studied. The results show that the development of mining-induced upward fractures can be divided into the following three stages: with the face advances from the open cut, the vertical fractures are generated at the mining boundary, and the roof is flexural but not caved; it is “Fractures generate stage.” After roof caves, the upward fractures extend and develop upward along the caving angle with continue advances; it is “Fractures develop and extend stage.” When the face reaches critical mining, the development height of the upward fractures is at its maximum and is basically invariable; it is “Fractures stabilization stage.” Mining-induced fractures can be analyzed as mixed-type fractures in fracture mechanics; when the combined stress exceeds the critical strength of stratum, it will extend downward until penetrate through the stratum, and the upward fracture develops and extends upwards. The parameter controlling the fracture of the rock stratum is the maximum hoop tensile stress σ(θ)max, at the fracture end, the theoretical model of fracture propagation was established, and the criterion of upward fractures was proposed.

Major symptoms of depression are commonly observed in patients requiring total hip arthroplasty (THA), and this is associated with increased pain scores and opioid consumption. We aimed to investigate the analgesic effect of duloxetine in these high-risk patients.Among 263 patients scheduled for primary unilateral THA, 67 patients who scored at least 8 on the 17-item Hamilton Depression Scale (HAMD) were enrolled in this study. Patients were randomized to the duloxetine group (60 mg daily, from the day of surgery to postoperative day 6) or the placebo group. The postoperative visual analog scale (VAS) score during walking, the VAS score during hip flexion, and resting VAS score was measured. Postoperative morphine consumption, hip range of motion (ROM), Harris hip score (HHS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) function, postoperative length of stay (LOS), and adverse events were recorded.The duloxetine group had significantly lower VAS scores during walking and hip flexion from postoperative day 3 to week 3 than the placebo group. With regard to the resting VAS score, duloxetine showed a better analgesic effect from postoperative day 3 to week 2 than placebo. Patients in the duloxetine group had less consumption of morphine. The duloxetine group exhibited better hip function scores, including ROM, HHS, and WOMAC function scores than the placebo group. No significant difference was observed in LOS or adverse events between groups.Perioperative short-term duloxetine provides advantages in decreasing pain, reducing morphine consumption, and increasing hip function in THA patients who have depressive symptoms.

The near-surface anisotropy is one of the factors leading to an inaccurate velocity estimation in the shallow area, which has a strong impact on the static correction of land data and seismic imaging of the subsurface in depth. To investigate the anisotropy influence, the consideration of medium anisotropy in near-surface seismic modeling becomes necessary. In the oil and gas industry, finite-difference (FD) methods are commonly used for seismic wave modeling, thanks to their simplicity, accuracy, and high efficiency. However, for near-surface modeling, the implementation of free-surface boundary conditions and nonflat topography representation are the two main obstacles preventing the effectiveness of FD methods. To address these two issues in the vertical transversely isotropic anisotropic scenarios, we have developed a simple and efficient method for the discrete model design which can be easily applied to the conventional Cartesian-grid FD modeling. Our method involves: (1) the parameter-averaging method for implicitly implementing the stress-free condition by a modification of model anisotropy parameters near the (non) flat free-surface boundary and (2) an independent wavefield superposition with modeling results of different parameter configurations to accurately represent the rugged topography and significantly reduce the staircase diffractions caused by a staircase approximation of continuous surface in the Cartesian-grid discretization. For validation of this method, we conduct several numerical tests in 2D and 3D spaces. The accuracy is demonstrated by a comparison of the spectral-element solutions of SPECFEM in modeling the seismic wave propagation in the presence of an irregular free surface. From the aspect of computational efficiency, it is more promising in practical applications due to the use of wavefield superposition strategy in this method which does not require finer spatial sampling to eliminate the staircase diffractions.

Spinal cord injury (SCI) is a serious disorder of the central nervous system with a high disability rate. Long noncoding RNAs (lncRNAs) are reported to mediate many biological processes. The aim of this study was to explore lncRNA and mRNA expression profiles and functional networks after SCI. Differentially expressed genes between SCI model rats and sham controls were identified by microarray assays and analyzed by functional enrichment. Key lncRNAs were identified using a support vector machine- (SVM-) recursive feature elimination (RFE) algorithm. A trans and cis regulation model was used to analyze the regulatory relationships between lncRNAs and their targets. An lncRNA-related ceRNA network was established. We identified 5465 differentially expressed lncRNAs (DE lncRNAs) and 8366 differentially expressed mRNAs (DE mRNAs) in the SCI group compared with the sham group ( fold change > 2.0 , p < 0.05 ). Four genes were confirmed by qRT-PCR which were consistent with the microarray data. GSEA analysis showed that most marked changes occurred in pathways related to immune inflammation and nerve cell function, including cytokine-cytokine receptor interaction, neuroactive ligand-receptor interaction, and GABAergic synapse. Enrichment analysis identified 30 signaling pathways, including those associated with immune inflammation response. A total of 40 key lncRNAs were identified using the SVM-RFE algorithm. A key lncRNA-mRNAs coexpression network was generated for 230 951 lncRNA-mRNA pairs with half showing positive correlations. Several key DE lncRNAs were predicted to have “cis”- or “trans”-regulated target genes. The transcription factors, Sp1, JUN, and SOX10, may regulate the interaction between XR_001837123.1 and ETS 1. In addition, five pairs of ceRNA regulatory sequences were constructed. Many mRNAs and lncRNAs were found to be dysregulated after SCI. Bioinformatic analysis showed that DE lncRNAs may play crucial roles in SCI. It is anticipated that these findings will provide new insights into the underlying mechanisms and potential therapeutic targets for SCI.

The matching degree between the zeolite channel size and the isomer size determines the product distribution of dodecane hydroisomerization.

The diffusion of Sulfate ions in concrete is a complex process and affects the performance of concrete. Experiments on the time-dependent distribution of sulfate ions in concrete under the coupling of pressure load, dry-wet circulation, and sulfate attack, and the diffusion coefficient of sulfate ions with various parameters was tested. The applicability of the cellular automata (CA) theory to simulate the diffusion of sulfate ions was discussed. In this paper, a multiparameter cellular automata (MPCA) model was developed to simulate the impacts of load, immersion ways, and sulfate solution concentration for the diffusion of sulfate ions in concrete. The MPCA model was compared with experimental data, considering compressive stress, sulfate solution concentration, and other parameters. The numerical simulations verify the calculation results based on the MPCA model are in good agreement with the test data. Finally, the applicability of the established MPCA model was also discussed.

This article summarizes recent efforts in developing enantioselective palladium- and nickel-catalyzed ring-opening/coupling reactions of cyclobutanones with a tethered aryl halide.

In this paper, we research theta function identity involving Rogers– Ramanujan identity and establish a Rogers–Ramanujan–Slater type theta function identity related to G(q) and φ(q).

The transition-metal-catalyzed synthesis of chiral silacycles is a challenging processes in organosilicon chemistry. Herein, we report a facile and regioselective synthesis of a novel class of 2,3-dihydrosilole derivatives with good yields via the palladium-catalyzed Heck-type reaction of silacyclopentenes (SCPs) with aryl iodides. Preliminary investigations on the enantioselective version of this palladium-catalyzed Heck-type process reveal that the presence of N-Boc-l-proline allows the diastereo- and enantioselective formation of chiral 2,3-dihydrosilole derivatives bearing both carbon and silicon-stereogenic centers.

Shale oil is becoming increasingly important in the global energy market, but its accumulation mechanism is not fully understood. We present novel and direct fluid inclusion data from the Lower Permian Fengcheng Formation, Mahu Sag, Junggar Basin, northwest China. Shortite veins in this source rock contain abundant two-phase gas-liquid hydrocarbon inclusions and coeval aqueous inclusions. The inclusions have highly variable degrees of bubble filling (5–80 vol% vapor) and homogenization temperature differences between oil and aqueous inclusions (~50 °C), which demonstrate that fluid (oil-gas-water) immiscibility occurred at high pressures. The hydrocarbon inclusions record different levels of fluid over-pressure (32.9–43.0 MPa), with a paleopressure coefficient of 1.3–1.7. Episodic fluid over-pressure release resulted in shale oil accumulation, with faults/fractures acting as important migration pathways. Oil from deeper and more mature source rocks within the Fengcheng Formation was expelled upward to the shale oil reservoir. These processes are common and important in shale oil systems. These results show that the accumulation of unconventional hydrocarbons occurs pervasively within the reservoirs, and fluid displacement is critical in exploration and exploitation.

Increasing evidence indicates close interaction between immune cells and the brain, revising the traditional view of the immune privilege of the brain. However, the specific mechanisms by which immune cells promote normal neural function are not entirely understood. Mucosal-associated invariant T cells (MAIT cells) are a unique type of innate-like T cell with molecular and functional properties that remain to be better characterized. In the present study, we report that MAIT cells are present in the meninges and express high levels of antioxidant molecules. MAIT cell deficiency in mice results in the accumulation of reactive oxidative species in the meninges, leading to reduced expression of junctional protein and meningeal barrier leakage. The presence of MAIT cells restricts neuroinflammation in the brain and preserves learning and memory. Together, our work reveals a new functional role for MAIT cells in the meninges and suggests that meningeal immune cells can help maintain normal neural function by preserving meningeal barrier homeostasis and integrity.

An increasing number of services are being offered which leads to difficulties in choosing appropriate services during mashup development. Currently, several service recommendation techniques have been developed for mashup creation, however, they are largely limited to suggesting services which have similar functionalities. The fundamental problem with these techniques is that they do not consider the large semantic gap between mashup descriptions and service descriptions. In this paper, we propose a compositional semantics-based service bundle recommendation model (CSBR) to tackle this problem. CSBR is based on a semantic service package repository, which is constructed by mining the existing mashups. Specifically, the reusable service packages, which consist of multiple collaborative services, are annotated with composite semantics rather than their original semantics. Based on the semantic service package repository, CSBR can recommend a bundle of services that cover the functional requirements of the mashup as completely as possible. Extensive experiments are conducted on a real-world dataset and the results show CSBR achieves significant performance improvements in both precision and recall metrics over the state-of-the-art methods.