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With the development of the times, traditional innovation and entrepreneurship education exist in the backwardness of education concept and learning concept. This paper proposes a model for entrepreneurship innovation that incorporates multi-source data fusion technology. From both online and offline sources, we obtain multi-source data about the education and teaching methods of the entrepreneurship innovation education concept in higher vocational colleges and universities. In the process of multi-source data fusion, data is preprocessed to improve its quality and efficiency during data fusion. Using the least squares method to complete the multi-source data fusion operation, combined with the concept of entrepreneurship innovation education, co-designed a data fusion-driven innovative entrepreneurship education teaching model that integrates interactive and targeted teaching methods. The model underwent validation and analysis. The data show that after some time of adopting the targeted teaching method to teach students innovative and entrepreneurial concepts, the difference between the mean value of the level of creative and entrepreneurial concepts of the students in the experimental group mean value (43.79) and the control group mean value (43.79) is 4.55. The sig value is 0.019

In innovation and entrepreneurship education, personalized Education is achieved through specialized creative integration and project-based learning to cultivate college students’ abilities in innovation, creation, and entrepreneurship. However, besides providing a wide range of course options and resources on the supply side, it is crucial to emphasize enhancing learners’ intrinsic motivation on the demand side of project-based learning. We conducted an educational practice to enhance students’ personalized learning inherent motivation in the medical school. Through assigning one project per student, we aimed to stimulate students’ curiosity, empathy, and sense of responsibility by focusing on the authenticity of project topics. Furthermore, the uniqueness of projects in innovation and creation was used to enhance students’ understanding of identification and ownership. Additionally, we promoted students’ courage to transform old habits, products, and services through a sense of belonging and conformity fostered within the student community. The timely supervision and rewards in competitions also contributed to students’ understanding of rhythm, fulfillment, and respect. After a project-based Practice, significant progress and improvements were observed in students’ professional abilities, multiple intelligences, creativity, and competition results.

The effect of Fe content on the microstructure and mechanical properties of Al-Mg-Si alloy cast rods at different solution temperatures was investigated by means of electronic tensile testing machine, metallographic microscope and transmission electron microscope. When Fe content is 0.14%（mass fraction, the same below）, Al-Mg-Si alloy has the highest strength and elongation. With the increase of solution temperature, the strength of the alloy increases continuously. When the solution temperature is above 520 ℃, the strength of the alloy tends to peak, the tensile strength is 280 MPa, the yield strength is 259 MPa, and the elongation is 13.40%. For the Al-Mg-Si alloy with Fe content of 0.14%, the Fe-rich phase at the grain boundary is spherical α-Al8Fe2Si, which has a weak cleavage effect on the alloy matrix, and its dispersion distribution plays a role in the grain boundary binding. When Fe content is lower than 0.14%, the spherical α-Al8Fe2Si at grain boundaries is very little, and the nailed grain boundaries are weak. When the solution above 500 ℃, the grains grow obviously, the elongation after fracture is greatly reduced. When the Fe content is higher than 0.14%, the Fe-rich phases are mostly long strips of β-Al5FeSi, which have a strong effect on the interface cleavage. With the increase of Fe content, the strength and post-fracture elongation of the alloy decrease continuously. In addition, Fe content affects the precipitation transition during the aging process of βʺ phase. When Fe content is 0.14%, the size of βʺ phase precipitation is small, the number is large, and the distribution is dense, which has the strongest hindering effect on dislocation movement.

The single-stage & two-stage solution and the single aging-tensile property curves at 110-135 ℃ were studied by using the 7A36 aluminum alloy extruded tube of ϕ250 mm×20 mm and ϕ340 mm×30 mm under industrial production conditions. The optimal heat treatment was adopted to compare the tensile properties of two kinds of aluminum alloy extruded tube.The phase transition temperature was measured by DSC, and the microstructure and tensile fracture were observed by OM, SEM and TEM.The results show that the tensile strength, yield strength and elongation of 7A36 alloy extruded tube can reach 696, 655 MPa and 14.0%, respectively, under the optimal heat treatment. Compared with the process of direct chill casting (DC) ingot & extrusion with high extrusion ratio, the size of grain and precipitated phase is smaller, the width of precipitation free zone is narrower under the process of forging ingot & conventional extrusion, which significantly affects the strength.At the same time, the alloy shows high quenching sensitivity. During solution treatment, quenching micro-cracks are easily induced near Fe-rich phase, which significantly affects the elongation of alloy extruded tube.

This article discusses the development and validation of a prognostic model for predicting flares in generalized pustular psoriasis (GPP). GPP is a rare auto-inflammatory skin disease characterized by recurrent flares of neutrophil-filled sterile pustules. These flares can have a significant impact on the daily activities and overall well-being of patients and can lead to life-threatening complications if left untreated. The study aimed to identify risk factors for GPP flare and construct a predictive model based on clinical characteristics to forecast the occurrence of flares. The model incorporates four features: history of psoriasis vulgaris, risky alcohol use, temperature at fever, and albumin levels. The model achieved promising results in internal and external validation processes and may provide critical insights into GPP flare patterns and help prevent such episodes. [Extracted from the article]