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The rapid development of modern society is inseparable from information technology, and most of this information technology is based on big data, which makes the teaching field in the new era keep pace with the times and brings great changes to the academic activities in which teachers and students participate, as well as to the quality of their thinking skills, and thus, likely even their overall lives. Under the background of big data, through the effective application of relevant technologies, students’ learning is no longer limited to a relatively single traditional teaching level, and teaching needs strategic innovation. This paper improves the mathematical model of precision teaching strategy, establishes the empirical model of the optimal mode of College English teaching based on big data and puts forward relevant innovative teaching methods. Through the rational use of big data technology, the content and form of College English classroom teaching can be improved, so as to improve the quality of College English teaching.

Summary: Chimeric antigen receptor (CAR)‐T‐cell therapy has demonstrated considerable efficacy and safety in the treatment of patients with relapsed/refractory haematological malignancies. Owing to significant advances, CAR‐T‐cell therapeutic modality has undergone substantial shifts in its clinical application. Coagulation abnormalities, which are prevalent complications in CAR‐T‐cell therapy, can range in severity from simple abnormalities in coagulation parameters to serious haemorrhage or disseminated intravascular coagulation associated with life‐threatening multiorgan dysfunction. Nonetheless, there is a lack of a comprehensive overview concerning the coagulation abnormalities associated with CAR‐T‐cell therapy. With an aim to attract heightened clinical focus and to enhance the safety of CAR‐T‐cell therapy, this review presents the characteristics of the coagulation abnormalities associated with CAR‐T‐cell therapy, including clinical manifestations, coagulation parameters, pathogenesis, risk factors and their influence on treatment efficacy in patients receiving CAR‐T‐cell infusion. Due to limited data, these conclusions may undergo changes as more experience accumulates. [ABSTRACT FROM AUTHOR]

Multi-modal object re-identification (ReID) is a challenging task that seeks to identify objects across different image modalities by leveraging their complementary information. Traditional CNN-based methods are constrained by limited receptive fields, whereas Transformer-based approaches are hindered by high computational demands and a lack of convolutional biases. To overcome these limitations, we propose a novel fusion framework named MambaReID, integrating the strengths of both architectures with the effective VMamba. Specifically, our MambaReID consists of three components: Three-Stage VMamba (TSV), Dense Mamba (DM), and Consistent VMamba Fusion (CVF). TSV efficiently captures global context information and local details with low computational complexity. DM enhances feature discriminability by fully integrating inter-modality information with shallow and deep features through dense connections. Additionally, with well-aligned multi-modal images, CVF provides more granular modal aggregation, thereby improving feature robustness. The MambaReID framework, with its innovative components, not only achieves superior performance in multi-modal object ReID tasks, but also does so with fewer parameters and lower computational costs. Our proposed MambaReID's effectiveness is validated by extensive experiments conducted on three multi-modal object ReID benchmarks. [ABSTRACT FROM AUTHOR]

Purpose: To determine the current status of vitamin D status and the associated factors for its deficiency among Chinese hospital staff. Methods: The physical examination data of 2509 hospital staff members was analyzed alongside that of 1507 patients who visited the hospital during the corresponding period of the examination. Serum concentration of 25-hydroxyvitamin D (25(OH)D) were measured in the participants. The hospital staff also completed surveys about general information, laboratory examination, and occupational characteristics. Results: The median vitamin D status (serum 25(OH)D concentration) of the participants was 9.0 ng/mL, ranging from 6.5 to 44.7 ng/mL, and the prevalence of deficiency (< 12.3 ng/mL) was 81.47% (2044/2509). The multivariable logistic regression revealed that nurses (OR = 1.54, 95% CI 1.09– 2.19, p = 0.015), BMI below 18 (OR = 2.39, 95% CI 1.02– 5.58, p = 0.045) associated with higher prevalence of vitamin D deficiency. In the contrast, age above 30 (OR = 0.69, 95% CI 0.53– 0.91, p = 0.009) and a high level of uric acid (OR = 0.56, 95% CI 0.41– 0.78, p = 0.001) associated with lower prevalence of vitamin D deficiency. The prevalence of vitamin D deficiency was higher among the hospital staff (81.47%) compared to the patients who visited the hospital during the same time period (65.69%). A substantial disparity was observed in the propensity score matching dataset (69.14% vs 79.94%, p < 0.001). Conclusion: Hospital staff are a high-risk group for vitamin D deficiency. Paying attention to vitamin D status and supplementation of this vitamin are pertinent aspects of hospital staff health care. Outdoor activities, vitamin D supplementation, and foods rich in vitamin D should be advocated. [ABSTRACT FROM AUTHOR]