Charge Transfer Fluctuations as a Signal for QGP

In this work, the charge transfer fluctuation which was previously used for $pp$ collisions is proposed for relativistic heavy-ion collisions as a QGP probe. We propose the appearance of a local minimum at midrapidity for the charge transfer fluctuation as a signal for a QGP. Within a two-component neutral cluster model, we demonstrate that the charge transfer fluctuation can detect the presence of a QGP as well as the size of the QGP in the rapidity space. We also show that the forward-backward correlation of multiplicity can be a similarly good measure of the presence of a QGP. Further, we show that the previously proposed net charge fluctuation is sensitive to the existence of the second phase only if the QGP phase occupies a large portion of the available rapidity space.Comment: 15 pages, 14 figures, to be submitte

Detecting QGP with charge transfer fluctuations

In this study, we analyze the recently proposed charge transfer fluctuations within a finite pseudo-rapidity space. As the charge transfer fluctuation is a measure of the local charge correlation length, it is capable of detecting inhomogeneity in the hot and dense matter created by heavy ion collisions. We predict that going from peripheral to central collisions, the charge transfer fluctuations at midrapidity should decrease substantially while the charge transfer fluctuations at the edges of the observation window should decrease by a small amount. These are consequences of having a strongly inhomogeneous matter where the QGP component is concentrated around midrapidity. We also show how to constrain the values of the charge correlations lengths in both the hadronic phase and the QGP phase using the charge transfer fluctuations

Research on Application of Kansei Image of Culture in Big data of Product Design

In pursuit of internationalization and globalization, the multinational corporations have begun to take into account the cultural differences between different regions for their product design and marketing strategy. This paper further clarifies the difference between the Kansei preferences and tendencies of consumers through the discussion on the relationship between products and the Kansei demand of consumers with different cultural backgrounds. In addition, in this paper, the Kansei demand of consumers will be learned through collecting the Kansei images of customers with different cultural backgrounds and learning about the differences of Kansei image affected by different cultural backgrounds and the Kansei factors such as the thoughts and feeling preferences of consumers under the influences of local cultures. Then, the factors affecting the Kansei demands of consumers with different cultural backgrounds are correctly analyzed, which will be helpful for the designers to master these design elements and apply them into product shape and functions, thereby designing the products that meet the consumers’ expectations and improving the additional values of the products

Charge Transfer Fluctuations as a QGP Signal

In this study, we analyze the recently proposed charge transfer fluctuations within a finite pseudo-rapidity space. As the charge transfer fluctuation is a measure of the local charge correlation length, it is capable of detecting inhomogeneity in the hot and dense matter created by heavy ion collisions. We predict that going from peripheral to central collisions, the charge transfer fluctuations at midrapidity should decrease substantially while the charge transfer fluctuations at the edges of the observation window should decrease by a small amount. These are consequences of having a strongly inhomogeneous matter where the QGP component is concentrated around midrapidity. We also show how to constrain the values of the charge correlations lengths in both the hadronic phase and the QGP phase using the charge transfer fluctuations. Current manuscript is based on the preprints hep-ph/0503085 (to appear in Physical Review C) and nucl-th/0506025.Comment: To appear in the proceedings of 18th International Conference on Ultrarelativistic Nucleus-Nucleus Collisions: Quark Matter 2005 (QM 2005), Budapest, Hungary, 4-9 Aug 200

Hyperspectral and Multispectral Image Fusion Using the Conditional Denoising Diffusion Probabilistic Model

Hyperspectral images (HSI) have a large amount of spectral information reflecting the characteristics of matter, while their spatial resolution is low due to the limitations of imaging technology. Complementary to this are multispectral images (MSI), e.g., RGB images, with high spatial resolution but insufficient spectral bands. Hyperspectral and multispectral image fusion is a technique for acquiring ideal images that have both high spatial and high spectral resolution cost-effectively. Many existing HSI and MSI fusion algorithms rely on known imaging degradation models, which are often not available in practice. In this paper, we propose a deep fusion method based on the conditional denoising diffusion probabilistic model, called DDPM-Fus. Specifically, the DDPM-Fus contains the forward diffusion process which gradually adds Gaussian noise to the high spatial resolution HSI (HrHSI) and another reverse denoising process which learns to predict the desired HrHSI from its noisy version conditioning on the corresponding high spatial resolution MSI (HrMSI) and low spatial resolution HSI (LrHSI). Once the training is completes, the proposed DDPM-Fus implements the reverse process on the test HrMSI and LrHSI to generate the fused HrHSI. Experiments conducted on one indoor and two remote sensing datasets show the superiority of the proposed model when compared with other advanced deep learningbased fusion methods. The codes of this work will be opensourced at this address: https://github.com/shuaikaishi/DDPMFus for reproducibility

Advances in exercise-induced vascular adaptation: mechanisms, models, and methods

Insufficient physical activity poses a significant risk factor for cardiovascular diseases. Exercise plays a crucial role in influencing the vascular system and is essential for maintaining vascular health. Hemodynamic stimuli generated by exercise, such as shear stress and circumferential stress, directly impact vascular structure and function, resulting in adaptive changes. In clinical settings, incorporating appropriate exercise interventions has become a powerful supplementary approach for treating and rehabilitating various cardiovascular conditions. However, existing models for studying exercise-induced vascular adaptation primarily rely on in vivo animal and in vitro cellular models, each with its inherent limitations. In contrast, human research faces challenges in conducting mechanistic analyses due to ethics issues. Therefore, it is imperative to develop highly biomimetic in vitro/ex vivo vascular models that can replicate exercise stimuli in human systems. Utilizing various vascular assessment techniques is also crucial to comprehensively evaluate the effects of exercise on the vasculature and uncover the molecular mechanisms that promote vascular health. This article reviews the hemodynamic mechanisms that underlie exercise-induced vascular adaptation. It explores the advancements in current vascular models and measurement techniques, while addressing their future development and challenges. The overarching goal is to unravel the molecular mechanisms that drive the positive effects of exercise on the cardiovascular system. By providing a scientific rationale and offering novel perspectives, the aim is to contribute to the formulation of precise cardiovascular rehabilitation exercise prescriptions