The Media Images of Old Influencers on TikTok:A Multimodal Critical Discourse Analysis

Drawing on the insights from multimodal critical discourse analysis,this study mainly focuses on two super-gerontic celebrities by selecting 60 videos to elucidate how their images are represented through linguistic(e.g.,captions,and hashtags)and other semiotic resources(e.g.,accessories,semiotic tools,and etc.).The findings suggest that images of the old celebrities are characterized as being attractive,wise,stylish,healthy and young,indicating that they are breaking up the stereotypical images of old people who are unattractive,dependent and senile.The phenomenon of old influencers making themselves visible on the social media suggests that they are moving towards successful aging with the backdrop of aging society in China.This present study suggests that multimodal construction of old celebrities can inform relevant practice to combat ageism in the media and helps to empower the old people in the media discourse.In doing so,the pedagogical implication of present study lies in its education about how we view aging in the aging society.

Response of saturated porous media subjected to local thermal loading on the surface of semi-infinite space

Heat source function method is adopted in the present paper to derive elementary solutions of coupled thermo-hydro-mechanical consolidation for saturated porous media under conjunct actions of instantaneous point heat source, instantaneous point fluid source and constant volume force. By using the so-called fictitious heat source method and images method, the solutions of a semi-infinite saturated porous medium subjected to a local heat source with time-varied intensity on its free surface are developed from elementary solutions. The numerical integral methods for calculating the unsteady temperature, pore pressure and displacement fields are given. The thermomechanical response are analyzed for the case of a circular planar heat source. Besides, the thermal consolidation characteristics of a saturated porous medium subjected to a harmonic thermal loading are also given, and the fluctuation processes of the field variables located below the center of heat source are analyzed.

Exploiting the point spread function for optical imaging through a scattering medium based on deconvolution method

Visual perception of humans penetrating turbid medium is hampered by scattering.Various techniques have been prompted recently to recover optical imaging through turbid materials.Among them,speckle correlation based on deconvolution is one of the most attractive methods taking advantage of high imaging quality,robustness,eas-of-use,and ease-of-integration.By exploiting the point spread function(PSF)of the scattering system,large Field-of-View,extended Depth-of-Field,noninvasiveness and spectral resoluation are now available as successful solutions for high quality and multifunctional image reconstruction.In this paper,we review the progress of imaging through a scattering medium based on deconvolution method,including the principle,the breakthrough of the limitation of the optical memory ffect,the improvement of the deconvolution algorithm and innovative applications.

Real-Time Underwater Image Enhancement Using Adaptive Full-Scale Retinex

Current Retinex-based image enhancement methods with fixed scale filters cannot adapt to situations involving various depths of field and illuminations.In this paper,a simple but effective method based on adaptive full-scale Retinex(AFSR)is proposed to clarify underwater images or videos.First,we design an adaptive full-scale filter that is guided by the optical transmission rate to estimate illumination components.Then,to reduce the computational complexity,we develop a quantitative mapping method instead of non-linear log functions for directly calculating the reflection component.The proposed method is capable of real-time processing of underwater videos using temporal coherence and Fourier transformations.Compared with eight state-of-the-art clarification methods,our method yields comparable or better results for image contrast enhancement,color-cast correction and clarity.

Learning-based lensless imaging through optically thick scattering media

The problem of imaging through thick scattering media is encountered in many disciplines of science,ranging from mesoscopic physics to astronomy.Photons become diffusive after propagating through a scattering medium with an optical thickness of over 10 times the scattering mean free path.As a result,no image but only noise-like patterns can be directly formed.We propose a hybrid neural network for computational imaging through such thick scattering media,demonstrating the reconstruction of image information from various targets hidden behind a white polystyrene slab of 3 mm in thickness or 13.4 times the scattering mean free path.We also demonstrate that the target image can be retrieved with acceptable quality from a very small fraction of its scattered pattern,suggesting that the speckle pattern produced in this way is highly redundant.This leads to a profound question of how the information of the target being encoded into the speckle is to be addressed in future studies.

Round-trip imaging through scattering media based on optical transmission matrix

Traditional one-way imaging methods become invalid when a target object is completely hidden behind scattering media. In this case, it has been much more challenging, since the light wave is distorted twice.To solve this problem, we propose an imaging method, so-called round-trip imaging, based on the optical transmission matrix of the scattering medium. We show that the object can be recovered directly from the distorted output wave, where no scanning is required during the imaging process. We predict that this method might improve the imaging speed and have potential application for real-time imaging.

Improvement of predictions of petrophysical transport behavior using three-dimensional finite volume element model with micro-CT images

Due to the intricate structure of porous media, the macroscopic petrophysical transport properties such as the permeability and the saturation used for the reservoir prediction also show a very complex nature and are difficult to obtain. Thus, a better understanding of the influence of the rock structure on the petrophysical transport properties is important. In this paper, we present a universal finite volume element modeling approach to reconstruct the three dimensional pore models from the micro-CT images based on the commercial software Mimics and ICEM, prior to the pore network model based on some basic assumptions. Moreover, tetra finite volume elements are piled up to realize the geometry reconstruction and the meshing process. Compared with the former methods, this process avoids the tremendously large storage requirement for the reconstructed porous geometry and the failures of meshing these complex polygon geometries, and at the same time improves the predictions of petrophysical transport behaviors. The model is tested on two Berea sandstones, four sandstone samples, two carbonate samples, and one Synthetic Silica. Single- and two phase flow simulations are conducted based on the Navier-Stokes equations in the Fluent software. Good agreements are obtained on both the network structures and predicted single- and two- phase transport properties against benchmark experimental data.