Active vibration control of support sting in wind tunnel by using adaptive method

The low-frequency and large-amplitude coupled vibration of the support sting in wind tunnel affects the accuracy of the wind tunnel test’s data. An active vibration control system of support sting in wind tunnel is demonstrated using adaptive control method in this paper. Following the establishment of the finite element model, and the extraction of parameter matrix, the original model is reduced to lower-mode model which contains first two pitching modes based on DC gain ranking method. The active control model is proposed based on model reference adaptive control method (RACM) to control the low-frequency vibration of supporting sting in wind tunnel. Research results have justified the effectiveness of the controlled system and provided insight into the practical application of the proposed method

Direct Measure of Giant Magnetocaloric Entropy Contributions in Ni-Mn-In

Off-stoichiometric alloys based on Ni 2 MnIn have drawn attention due to the coupled first order magnetic and structural transformations, and the large magnetocaloric entropy associated with the transformations. Here we describe calorimetric and magnetic studies of four compositions. The results provide a direct measure of entropy changes contributions including at the first-order phase transitions, and thereby a determination of the maximum field-induced entropy change corresponding to the giant magnetocaloric effect. We find a large excess entropy change, attributed to magneto-elastic coupling, but only in compositions with no ferromagnetic order in the high-temperature austenite phase. Furthermore, a molecular field model corresponding to antiferromagnetism of the low-temperature phases is in good agreement, and nearly independent of composition, despite significant differences in overall magnetic response of these materials

Street Stall Economy in China in the COVID-19 Era: Dilemmas and the International Experience of Promoting the Normalization of Street Stall Economy

Compared with those major policies that need to be practiced over the years, the street stall economy is more like a special means after the epidemic, resulting in a “short and brilliant” heat. Nevertheless, the street stall economy revives is facing several dilemmas. This paper reveals the dilemma of the prosperity and development of the stall economy before and after the epidemic, followed by the international experience and enlightenment of promoting the normalization of street stall economy, ranging from street vendor’s legal status and road administrative promotion to street food safety and environmental protection. To sum up, employment is the foundation of people’s livelihood and the source of wealth, hence, stall economy plays an indispensable role to create a win-win working world and promote the formation of a sustainable economic

Calorimetric and magnetic study for Ni50_{50}Mn36_{36}In14_{14} and relative cooling power in paramagnetic inverse magnetocaloric systems

The non-stoichiometric Heusler alloy Ni$_{50}$Mn$_{36}$In$_{14}$ undergoes a martensitic phase transformation in the vicinity of 345 K, with the high temperature austenite phase exhibiting paramagnetic rather than ferromagnetic behavior, as shown in similar alloys with lower-temperature transformations. Suitably prepared samples are shown to exhibit a sharp transformation, a relatively small thermal hysteresis, and a large field-induced entropy change. We analyzed the magnetocaloric behavior both through magnetization and direct field-dependent calorimetry measurements. For measurements passing through the first-order transformation, an improved method for heat-pulse relaxation calorimetry was designed. The results provide a firm basis for the analytic evaluation of field-induced entropy changes in related materials. An analysis of the relative cooling power (RCP), based on the integrated field-induced entropy change and magnetizing behavior of the Mn spin system with ferromagnetic correlations, shows that a significant RCP may be obtained in these materials by tuning the magnetic and structural transformation temperatures through minor compositional changes or local order changes

Nonexistence of Vortices for Rotating Two-Component Focusing Bose Gases

This paper is concerned with ground states of two-component Bose gases confined in a harmonic trap $V(x)=x_1^2+\Lambda^2 x_2^2$ rotating at the velocity $\Omega >0$, where $\Lambda\ge 1$ and $(x_1, x_2)\in R^2$. We focus on the case where the intraspecies interaction $(-a_1,-a_2)$ and the interspecies interaction $-\beta$ are both attractive, i.e, $a_1, a_2$ and $\beta$ are all positive. It is shown that for any $0<\Omega <\Omega ^*:=2$, ground states exist if and only if $0<a_1,\, a_2<a^*:=\|w\|^2_2$ and $00$ is the unique positive solution of $-\Delta w+ w-w^3=0$ in $R^2$. By developing the argument of refined expansions, we further prove the nonexistence of vortices for ground states as $\beta\nearrow\beta^*$, where $0<\Omega <\Omega ^*$ and $0<a_1,\, a_2<a^*$ are fixed.Comment: 59 pages, 1 figure, and all comments are welcom

Reconstruct-and-Generate Diffusion Model for Detail-Preserving Image Denoising

Image denoising is a fundamental and challenging task in the field of computer vision. Most supervised denoising methods learn to reconstruct clean images from noisy inputs, which have intrinsic spectral bias and tend to produce over-smoothed and blurry images. Recently, researchers have explored diffusion models to generate high-frequency details in image restoration tasks, but these models do not guarantee that the generated texture aligns with real images, leading to undesirable artifacts. To address the trade-off between visual appeal and fidelity of high-frequency details in denoising tasks, we propose a novel approach called the Reconstruct-and-Generate Diffusion Model (RnG). Our method leverages a reconstructive denoising network to recover the majority of the underlying clean signal, which serves as the initial estimation for subsequent steps to maintain fidelity. Additionally, it employs a diffusion algorithm to generate residual high-frequency details, thereby enhancing visual quality. We further introduce a two-stage training scheme to ensure effective collaboration between the reconstructive and generative modules of RnG. To reduce undesirable texture introduced by the diffusion model, we also propose an adaptive step controller that regulates the number of inverse steps applied by the diffusion model, allowing control over the level of high-frequency details added to each patch as well as saving the inference computational cost. Through our proposed RnG, we achieve a better balance between perception and distortion. We conducted extensive experiments on both synthetic and real denoising datasets, validating the superiority of the proposed approach