Integration of Social Media News Mining and Text Mining Techniques to Determine a Corporate’s Competitive Edge

Market globalization have triggered much more severe challenges for corporates than ever before. Thus, how to survive in this highly fluctuating economic atmosphere is an attractive topic for corporate managers, especially when an economy goes into a severe recession. One of the most consensus conclusions is to highly integrate a corporate’s supply chain network, as it can facilitate knowledge circulation, reduce transportation cost, increase market share, and sustain customer loyalty. However, a corporate’s supply chain relations are unapparent and opaque. To solve such an obstacle, this study integrates text mining (TM) and social network analysis (SNA) techniques to exploit the latent relation among corporates from social media news. Sequentially, this study examines its impact on corporate operating performance forecasting. The empirical result shows that the proposed mechanism is a promising alternative for performance forecasting. Public authorities and decision makers can thus consider the potential implications when forming a future policy

Towards Optimizing with Large Language Models

In this work, we conduct an assessment of the optimization capabilities of LLMs across various tasks and data sizes. Each of these tasks corresponds to unique optimization domains, and LLMs are required to execute these tasks with interactive prompting. That is, in each optimization step, the LLM generates new solutions from the past generated solutions with their values, and then the new solutions are evaluated and considered in the next optimization step. Additionally, we introduce three distinct metrics for a comprehensive assessment of task performance from various perspectives. These metrics offer the advantage of being applicable for evaluating LLM performance across a broad spectrum of optimization tasks and are less sensitive to variations in test samples. By applying these metrics, we observe that LLMs exhibit strong optimization capabilities when dealing with small-sized samples. However, their performance is significantly influenced by factors like data size and values, underscoring the importance of further research in the domain of optimization tasks for LLMs

Thermal-Mechanical Properties of Polyurethane-Clay Shape Memory Polymer Nanocomposites

Shape memory nanocomposites of polyurethane (PU)-clay were fabricated by melt mixing of PU and nano-clay. Based on nano-indentation and microhardness tests, the strength of the nanocomposites increased dramatically as a function of clay content, which is attributed to the enhanced nanoclay–polymer interactions. Thermal mechanical experiments demonstrated good mechanical and shape memory effects of the nanocomposites. Full shape memory recovery was displayed by both the pure PU and PU-clay nanocomposites.

The decay property of the X(3842)X(3842) as the ψ3(13D3)\psi_{_3}(1^3D_{_3}) state

In this paper, the new particle $X(3842)$ discovered by the LHCb Collaboration is identified to be the $\psi_{_3}(1^3D_{_3})$ state. We study its strong decays with the combination of the Bethe-Salpeter method and the $^3P_{_0}$ model. Its electromagnetic (EM) decay is also calculated by the Bethe-Salpeter method within Mandelstam formalism. The strong decay widths are {$\Gamma[X(3842)\rightarrow D^{0}\bar{D}^{0}]=1.28$ MeV}, $\Gamma[X(3823)\rightarrow D^{+}D^{-}]=1.08$ MeV, and the ratio ${\cal B}[X(3842)\rightarrow D^{+}D^{-}]/{\cal B}[X(3823)\rightarrow D^{0}\bar{D}^{0}]=0.84$. The EM decay width is $\Gamma[X(3842)\rightarrow\chi_{_{c2}}\gamma]=0.29$ MeV. We also estimate the total width to be 2.87 MeV, which is in good agreement with the experimental data $2.79^{+0.86}_{-0.86}$ MeV. Since the used relativistic wave functions include different partial waves, we also study the contributions of different partial waves in electromagnetic decay.Comment: 17 pages, 3 figures, 3 table

The electromagnetic decays of X(3823)X(3823) as the ψ2(13D2)\psi_2(1^{3}D_{2}) state and its radial excited states

We study the electromagnetic (EM) decays of $X(3823)$ as the $\psi_2(1^{3}D_{2})$ state by using the relativistic Bethe-Salpeter method. Our results are $\Gamma[X(3823)\rightarrow\chi_{_{c0}}\gamma]=1.6$ keV, $\Gamma[X(3823)\rightarrow\chi_{_{c1}}\gamma]=265$ keV, $\Gamma[X(3823)\rightarrow\chi_{_{c2}}\gamma]=57$ keV and $\Gamma[X(3823)\rightarrow\eta_{_c}\gamma]=1.3$ keV. The ratio ${\cal B}[X(3823)\rightarrow\chi_{_{c2}}\gamma]/{\cal B}[X(3823)\rightarrow\chi_{_{c1}}\gamma]=0.22$, agrees with the experimental data. Similarly, the EM decay widths of $\psi_{_2}(n^{3}D_{_2})$, $n=2,3$, are predicted, and we find the dominant decays channels are $\psi_{_2}(n^{3}D_{_2})\rightarrow\chi_{_{c1}}(nP)\gamma$, where $n=1,2,3$. The wave function include different partial waves, which means the relativistic effects are considered. We also study the contributions of different partial waves.Comment: 20 pages, 6 figures, 9 table