212 research outputs found
Homogeneous ACM bundles on exceptional isotropic Grassmannians
In this paper, we characterize homogeneous arithmetically Cohen-Macaulay
(ACM) bundles over exceptional isotropic Grassmannians in terms of their
associated data. We show that there are only finitely many irreducible
homogeneous ACM bundles by twisting line bundles over exceptional isotropic
Grassmannians. As a consequence, we prove that some exceptional isotropic
Grassmannians are of wild representation type.Comment: 18 pages. arXiv admin note: text overlap with arXiv:2206.0917
Data-driven model construction for anisotropic dynamics of active matter
The dynamics of cellular pattern formation is crucial for understanding
embryonic development and tissue morphogenesis. Recent studies have shown that
human dermal fibroblasts cultured on liquid crystal elastomers can exhibit an
increase in orientational alignment over time, accompanied by cell
proliferation, under the influence of the weak guidance of a molecularly
aligned substrate. However, a comprehensive understanding of how this order
arises remains largely unknown. This knowledge gap may be attributed, in part,
to a scarcity of mechanistic models that can capture the temporal progression
of the complex nonequilibrium dynamics during the cellular alignment process.
The orientational alignment occurs primarily when cells reach a high density
near confluence. Therefore, for accurate modeling, it is crucial to take into
account both the cell-cell interaction term and the influence from the
substrate, acting as a one-body external potential term. To fill in this gap,
we develop a hybrid procedure that utilizes statistical learning approaches to
extend the state-of-the-art physics models for quantifying both effects. We
develop a more efficient way to perform feature selection that avoids testing
all feature combinations through simulation. The maximum likelihood estimator
of the model was derived and implemented in computationally scalable algorithms
for model calibration and simulation. By including these features, such as the
non-Gaussian, anisotropic fluctuations, and limiting alignment interaction only
to neighboring cells with the same velocity direction, this model
quantitatively reproduce the key system-level parameters--the temporal
progression of the velocity orientational order parameters and the variability
of velocity vectors, whereas models missing any of the features fail to capture
these temporally dependent parameters.Comment: 20 pages, 14 figure
Research on the Mechanism of Entrepreneurship Education on College Students’ Entrepreneurial Willingness and Its Future Prediction
The strength of college students’ entrepreneurial willingness is a barometer for measuring the effectiveness of entrepreneurship education. It is also an important avenue for college students to expand their employment opportunities and enhance the quality of their employment in the face of new employment trends. Comprehensive universities offer a wide range of disciplines and great professional specialization. It is of great significance to explore the diversity results in college students’ entrepreneurship education indicators. According to the data on the relationship between entrepreneurial education and entrepreneurship willingness in comprehensive universities in Jiangsu province, various factors such as subject characteristics, work experience, educational background, and family environment significantly impact college students’ willingness to become entrepreneurs. The implementation of entrepreneurship education, including the awakening of entrepreneurial consciousness, the cultivation of entrepreneurial abilities, and the improvement of entrepreneurial willingness, has a direct impact on college students’ willingness to start their own businesses
DesignGPT: Multi-Agent Collaboration in Design
Generative AI faces many challenges when entering the product design
workflow, such as interface usability and interaction patterns. Therefore,
based on design thinking and design process, we developed the DesignGPT
multi-agent collaboration framework, which uses artificial intelligence agents
to simulate the roles of different positions in the design company and allows
human designers to collaborate with them in natural language. Experimental
results show that compared with separate AI tools, DesignGPT improves the
performance of designers, highlighting the potential of applying multi-agent
systems that integrate design domain knowledge to product scheme design
Lithium-Excess Research of Cathode Material Li2MnTiO4 for Lithium-Ion Batteries
Lithium-excess and nano-sized Li2+xMn1−x/2TiO4 (x = 0, 0.2, 0.4) cathode materials were synthesized via a sol-gel method. The X-ray diffraction (XRD) experiments indicate that the obtained main phases of Li2.0MnTiO4 and the lithium-excess materials are monoclinic and cubic, respectively. The scanning electron microscope (SEM) images show that the as-prepared particles are well distributed and the primary particles have an average size of about 20–30 nm. The further electrochemical tests reveal that the charge-discharge performance of the material improves remarkably with the lithium content increasing. Particularly, the first discharging capacity at the current of 30 mA g−1 increases from 112.2 mAh g−1 of Li2.0MnTiO4 to 187.5 mAh g−1 of Li2.4Mn0.8TiO4. In addition, the ex situ XRD experiments indicate that the monoclinic Li2MnTiO4 tends to transform to an amorphous state with the extraction of lithium ions, while the cubic Li2MnTiO4 phase shows better structural reversibility and stability
- …