Explore the vast range of titles available.

The dissolution kinetics of Al 2 O 3 in CaO-Al 2 O 3 -SiO 2 slags was studied using a high-temperature confocal scanning laser microscope at 1773 to 1873 K. The results show that the controlling step during the Al 2 O 3 dissolution was the diffusion in molten slag. It was found that the dissolution curves of Al 2 O 3 particles were hardly agreed with the traditional boundary layer diffusion model with the increase of the CaO/Al 2 O 3 ratio of slag. A modified diffusion equation considering slag viscosity was developed to study the dissolution mechanism of Al 2 O 3 in slag. Diffusion coefficients of Al 2 O 3 in slag were calculated as 2.8 × 10 −10 to 4.1 × 10 −10 m 2 /s at the temperature of 1773–1873 K. The dissolution rate of Al 2 O 3 increased with higher temperature, CaO/Al 2 O 3 , and particle size. A new model was shown to be v Al 2 O 3 = 0.16 × r 0 1.58 × x 3.52 × ( T − T mp ) 1.11 to predict the dissolution rate and the total dissolution time of Al 2 O 3 inclusions with various sizes, where v Al 2 O 3 is the dissolution rate of Al 2 O 3 in volume, µm 3 /s; x is the value of CaO/Al 2 O 3 mass ratio; R 0 is the initial radius of Al 2 O 3 , µm; T is the temperature, K; T mp is the melting point of slag, K.

To establish a bleeding prediction model for the use of low molecular weight heparin anticoagulation in cancer patients, aiming to help medical staff to individually evaluate the timing of low molecular weight heparin use in cancer patients. This retrospective cohort study enrolled 731 cancer patients (aged ≥18 years) from January to December 2021 receiving LMWH for venous thromboe-mbolism (VTE) prophylaxis at a tertiary general hospital in Southwest China. Participants were stratified into bleeding (n = 19) and non-bleeding (n = 712) cohorts based on ISTH-defined clinical outcomes. Risk factors identified through multivariablebinary logistic regression, with subsequent development and internal validation performed using R software (version 4.3.2). Univariate analysis of bleeding risk factors revealed statistically significant differences (P < 0.05) in body weight, nonsteroidal anti-inflammatory drug (NSAIDs) use, LMWH dosage, prothrombin time (PT), creatinine clearance, platelet count, Padua score, and HAS-BLED bleeding risk score. Based on clinical relevance, the final model incorporated LMWH dosage, platelet count, and HAS-BLED bleeding risk score as assessment items. The model demonstrated excellent predictive ability for bleeding events, with an ROC-AUC (95% CI) of 0.90 (0.82-0.97). The model showed good discrimination (Hosmer-Lemeshow, P = 0.854 > 0.05) and decision making capability, with strong diagnostic performance (accuracy: 0.83, sensitivity: 0.83, specificity: 0.79, positive predictive value: 0.99). The model had a low probability of missed diagnoses and high sensitivity and specificity. This study developed an optimized bleeding risk prediction model by enhancing the HAS-BLED score through the integration of three key variables: HAS-BLED score, LMWH dosage, and platelet count, demonstrating a robust application prospect for anticoagulation management in cancer patients.

Angiotensin-converting enzyme (ACE), a zinc metalloprotein, is a central component of the renin–angiotensin system (RAS). It degrades bradykinin and other vasoactive peptides. Angiotensin-converting-enzyme inhibitors (ACE inhibitors, ACEIs) decrease the formation of angiotensin II and increase the level of bradykinin, thus relaxing blood vessels as well as reducing blood volume, lowering blood pressure and reducing oxygen consumption by the heart, which can be used to prevent and treat cardiovascular diseases and kidney diseases. Nevertheless, ACEIs are associated with a range of adverse effects such as renal insufficiency, which limits their use. In recent years, researchers have attempted to reduce the adverse effects of ACEIs by improving the selectivity of ACEIs for structural domains based on conformational relationships, and have developed a series of novel ACEIs. In this review, we have summarized the research advances of ACE inhibitors, focusing on the development sources, design strategies and analysis of structure-activity relationships and the biological activities of ACE inhibitors.

Technological advancements are a key engine for improving productivity and are fundamental to enhancing the resilience of the agricultural economy by influencing production methods and driving structural transformation. The objective of this study is to analyze the impact of technological progress on agricultural economic resilience in China, with particular attention to (i) its direct effects on resistance, recovery, and reconstruction; (ii) its indirect effects through the upgrading of the agricultural industrial structure; and (iii) its potential nonlinear effects under different structural thresholds. To achieve this, a multidimensional evaluation framework has been developed to assess agricultural economic resilience through three distinct dimensions: resistance, recovery, and reconstruction. Using fixed effects, mediation, threshold and spatial Durbin models, we empirically analyze the impact pathways. The results suggest that technological progress significantly increases agricultural resilience, with robustness confirmed by various tests including model substitution and variable replacement. Furthermore, regional heterogeneity is evident, with the central region showing the strongest positive effect. The mediation analysis shows that modernization of industrial structure serves as an important transmission channel, while the threshold regression identifies nonlinear effects, with significant improvements occurring beyond certain structural thresholds. The results underline the importance of promoting technological innovation in agriculture, developing region-specific support measures and accelerating structural optimization to strengthen the resilience of agriculture.

Nanoparticles have unique physical and chemical properties and are currently widely used in disease diagnosis, drug delivery, and new drug development in biomedicine. In recent years, the role of nanomedical technology in cancer treatment has become increasingly obvious. Autophagy is a multi-step degradation process in cells and an important pathway for material and energy recovery. It is closely related to the occurrence and development of cancer. Because nanomaterials are highly targeted and biosafe, they can be used as carriers to deliver autophagy regulators; in addition to their favorable physicochemical properties, nanomaterials can be employed to carry autophagy inhibitors, reducing the breakdown of chemotherapy drugs by cancer cells and thereby enhancing the drug’s efficacy. Furthermore, certain nanomaterials can induce autophagy, triggering oxidative stress-mediated autophagy enhancement and cell apoptosis, thus constraining the progression of cancer cells.There are various types of nanoparticles, including liposomes, micelles, polymers, metal-based materials, and carbon-based materials. The majority of clinically applicable drugs are liposomes, though other materials are currently undergoing continuous optimization. This review begins with the roles of autophagy in tumor treatment, and then focuses on the application of nanomaterials with autophagy-regulating functions in tumor treatment.

The curvature estimates for k curvature equations with general right hand sides is a longstanding problem. In this paper, we give a proof of curvature estimates for n < 2 k base on a conjecture of a key inequality. At last, we proved the conjecture is true for k = n - 2 .

The curvature estimates for 𝑘 curvature equations with general right-hand sides is a longstanding problem. In this paper, we completely solve the problem when 𝑘 = 𝑛 − 1. We also discuss some applications of our estimates.

In the research of fully nonlinear elliptic partial differential equations, the concavities of the nonlinear operators is always essential. The concavity is the key to establish the curvature estimates of these equations. However, very few concave operators are known. In the present paper, some new examples are provided, which are the sum Hessian operators and the linear combination of k Hessian operators. We obtain the concavities and the quotient concavities of these new operators. As an application of our concavities, we establish the curvature estimates of convex solutions for the equations with general right-hand side defined by these new operators.

We prove that, in Minkowski space, if a spacelike, ( n - 1 ) -convex hypersurface M with constant σ n - 1 curvature has bounded principal curvatures, then M is convex. Moreover, if M is not strictly convex, after an R n , 1 rigid motion, M splits as a product M n - 1 × R .