Diffusion-based subsurface multiphysics monitoring and forecasting

Carbon capture and storage (CCS) plays a crucial role in mitigating greenhouse gas emissions, particularly from industrial outputs. Using seismic monitoring can aid in an accurate and robust monitoring system to ensure the effectiveness of CCS and mitigate associated risks. However, conventional seismic wave equation-based approaches are computationally demanding, which hinders real-time applications. In addition to efficiency, forecasting and uncertainty analysis are not easy to handle using such numerical-simulation-based approaches. To this end, we propose a novel subsurface multiphysics monitoring and forecasting framework utilizing video diffusion models. This approach can generate high-quality representations of CO$2$ evolution and associated changes in subsurface elastic properties. With reconstruction guidance, forecasting and inversion can be achieved conditioned on historical frames and/or observational data. Meanwhile, due to the generative nature of the approach, we can quantify uncertainty in the prediction. Tests based on the Compass model show that the proposed method successfully captured the inherently complex physical phenomena associated with CO$_2$ monitoring, and it can predict and invert the subsurface elastic properties and CO$_2$ saturation with consistency in their evolution

A prior regularized full waveform inversion using generative diffusion models

Full waveform inversion (FWI) has the potential to provide high-resolution subsurface model estimations. However, due to limitations in observation, e.g., regional noise, limited shots or receivers, and band-limited data, it is hard to obtain the desired high-resolution model with FWI. To address this challenge, we propose a new paradigm for FWI regularized by generative diffusion models. Specifically, we pre-train a diffusion model in a fully unsupervised manner on a prior velocity model distribution that represents our expectations of the subsurface and then adapt it to the seismic observations by incorporating the FWI into the sampling process of the generative diffusion models. What makes diffusion models uniquely appropriate for such an implementation is that the generative process retains the form and dimensions of the velocity model. Numerical examples demonstrate that our method can outperform the conventional FWI with only negligible additional computational cost. Even in cases of very sparse observations or observations with strong noise, the proposed method could still reconstruct a high-quality subsurface model. Thus, we can incorporate our prior expectations of the solutions in an efficient manner. We further test this approach on field data, which demonstrates the effectiveness of the proposed method

Secured green communication scheme for interference alignment based networks

In this paper, a new security and green communication scheme is proposed to the Interference-Alignment (IA) based networks. To achieve a secured communication, full-duplex receivers are utilized to transmit artificial noise (AN). Both the signals and the ANs are used to harvest energy to realize green communication. For these reasons, the feasible conditions of this scheme are analyzed first. Secondly, the average transmission rate, the secrecy performance and the harvested energy are investigated. Thirdly, an optimization scheme of simultaneous wireless information and power transfer (SWIPT) is given to optimize the information transmission and the energy harvesting efficiency. Meanwhile, an improved IA iteration algorithm is designed to eliminate both the AN and the interference. Furthermore, relay cooperation is considered and its system performance is analyzed. The simulations show that the target average transmission rate is not affected by AN, while the secrecy performance can be greatly improved. The energy harvesting efficiency is also better than the traditional schemes. As expected, the average transmission rate further is improved with the relay cooperation

Nasopharyngeal carcinoma with non-squamous phenotype may be a variant of nasopharyngeal squamous cell carcinoma after inhibition of EGFR/PI3K/AKT/mTOR pathway

Nasopharyngeal carcinoma (NPC) is a cancerous tumor that develops in the nasopharynx epithelium and typically has squamous differentiation. The squamous phenotype is evident in immunohisto-chemistry, with diffuse nuclear positivity for p63 and p40. Nonetheless, a few NPCs have been identified by clinicopathological diagnosis that do not exhibit the squamous phenotype; these NPCs are currently referred to as non-squamous immuno-phenotype nasopharyngeal carcinomas (NSNPCs). In a previous work, we have revealed similarities between the histological appearance, etiology, and gene alterations of NSNPC and conventional NPC. According to ultrastructural findings, NSNPC still falls under the category of non-keratinized squamous cell carcinoma that is undifferentiated. NSNPC has an excellent prognosis and a low level of malignancy, according to a retrospective investigation. Based on prior research, we investigated the molecular mechanism of NSNPC not expressing the squamous phenotype and its biological behavior. IHC was used to determine the expression of EGFR, PI3K, AKT, p-AKT, mTOR, p-mTOR, Notch, STAT3 and p-STAT3 in a total of 20 NSNPC tissue samples and 20 classic NPC tissue samples. We obtained human NPC cell lines (CNE-2,5-8F) and used EGFR overexpression plasmid and shRNAs to transfect them. To find out whether mRNA and proteins were expressed in the cells, we used Western blotting and qRT-PCR. Cell biological behavior was discovered using the CCK-8 assay, cell migration assay, and cell invasion assay. EGFR, PI3K, p-AKT and p-mTOR proteins were lowly expressed in NSNPC tissues by immunohistochemistry, compared with classical NPC. In the classical NPC cell lines CNE-2 and 5-8F, overexpression EGFR can up-regulate the expression of p63 through the PI3K/AKT/mTOR pathway, and promote the proliferation, migration, and invasion of nasopharyngeal carcinoma cells. At the same time, knockout of EGFR can down-regulate p63 expression through the PI3K/AKT/mTOR pathway, and inhibit the proliferation, migration, and invasion of nasopharyngeal carcinoma cells. The lack of p63 expression in NSNPC was linked with the inhibition of the EGFR/PI3K/AKT/mTOR pathway, and NSNPC may be a variant of classical NPC