Construction of VR/AR Smart Cloud Space based on 5G Network Environment in Education

With the emergence of the “5G+education” era, research on its application is mostly theoretical and lacks practical depth, making application research costly. This study aims to integrate school, third-party enterprises, and other resources to explore the joint building of specific application scenarios for “5G+education” in schools. The 5G VR/AR smart cloud space is a smart education experience scene that combines relevant teaching resources with teaching scenes through cloud rendering using virtual reality technology (VR) and augmented reality technology (AR). The high-speed and low-delay features of the 5G network and the support of cloud rendering technology enable students to experience virtual reality scenes through VR head-mounted displays while in the classroom, enhancing learning engagement. This study explores the application of 5G technology in primary school financial literacy education, studying its impact on environmental construction, resource application, curriculum development, and learning modes. Through theoretical and practical research, this study promotes education informatization development at the school and regional levels, benefiting students and teachers alike

Time-Varying Vector Error-Correction Models: Estimation and Inference

This paper considers a time-varying vector error-correction model that allows for different time series behaviours (e.g., unit-root and locally stationary processes) to interact with each other to co-exist. From practical perspectives, this framework can be used to estimate shifts in the predictability of non-stationary variables, test whether economic theories hold periodically, etc. We first develop a time-varying Granger Representation Theorem, which facilitates the establishment of asymptotic properties for the model, and then propose estimation and inferential methods and theory for both short-run and long-run coefficients. We also propose an information criterion to estimate the lag length, a singular-value ratio test to determine the cointegration rank, and a hypothesis test to examine the parameter stability. To validate the theoretical findings, we conduct extensive simulations. Finally, we demonstrate the empirical relevance by applying the framework to investigate the rational expectations hypothesis of the U.S. term structure

Time-varying multivariate causal processes

In this paper, we consider a wide class of time-varying multivariate causal processes that nests many classical and new examples as special cases. We first show the existence of a weakly dependent stationary approximation to initiate our theoretical investigation. We then consider a quasi-maximum likelihood estimation (QMLE), and provide both point-wise and uniform inferences to coefficient functions of interest. The theoretical findings are further examined through extensive simulations. Finally, we show empirical relevance of our study by evaluating both temporal and contemporaneous connectedness between the stock markets of China and U.S

Estimation of Semiparametric Multi-Index Models Using Deep Neural Networks

In this paper, we consider estimation and inference for both the multi-index parameters and the link function involved in a class of semiparametric multi-index models via deep neural networks (DNNs). We contribute to the design of DNN by i) providing more transparency for practical implementation, ii) defining different types of sparsity, iii) showing the differentiability, iv) pointing out the set of effective parameters, and v) offering a new variant of rectified linear activation function (ReLU), etc. Asymptotic properties for the joint estimates of both the index parameters and the link functions are established, and a feasible procedure for the purpose of inference is also proposed. We conduct extensive numerical studies to examine the finite-sample performance of the estimation methods, and we also evaluate the empirical relevance and applicability of the proposed models and estimation methods to real data

Original Article Synergy between IL-6 and TGF-β signaling promotes FOXP3 degradation

Abstract: The forkhead family transcription factor FOXP3 is critical for the differentiation and function of CD4 + CD25 + regulatory T cells (Treg). How FOXP3 protein level is negatively regulated under the inflammatory microenvironment is largely unknown. Here we report that the combination of transforming growth factor-beta (TGF-β) and IL-6 treatment (IL-6/TGF-β) can synergistically downregulate FOXP3 at the posttranslational level by promoting FOXP3 protein degradation. In our FOXP3 overexpression model, we found that IL-6/TGF-β treatment upregulated IL-6R expression but did not affect the stability of FOXP3 mRNA. Moreover, we found that the proteasome inhibitor MG132 could inhibit IL-6/TGF-β-mediated downregulation of FOXP3 protein, which reveals a potential pathway for modulating Treg activity by preventing FOXP3 degradation during inflammation

FOXP3 and RORγt: Transcriptional regulation of Treg and Th17

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Early-onset convulsive seizures induced by brain hypoxia-ischemia in aging mice: effects of anticonvulsive treatments

Sherpa Romeo green journal. Open access article. Creative Commons Attribution License applies.Aging is associated with an increased risk of seizures/epilepsy. Stroke(ischemic or hemorrhagic) and cardiac arrest related brain injury are two major causative factors for seizure development in this patient population. With either etiology, seizures area poor prognostic factor. In spite of this, the underlying pathophysiology of seizure development is not well understood. In addition, a standardized treatment regimen with anticonvulsants and outcome assessments following treatment has yet to be established for these post-ischemic seizures. Previous studies have modeled post-ischemic seizures in adult rodents, but similar studies in aging/aged animals, a group that mirrors a higher risk elderly population, remain sparse. Our study therefore aimed to investigate early-onset seizures in aging animals using a hypoxia-ischemia (HI) model. Male C57 black mice18-20-month-old underwent a unilateral occlusion of the common carotid artery followed by a systemic hypoxic episode (8% O2 for 30 min). Early-onset seizures were detected using combined behavioral and electroencephalographic (EEG) monitoring. Brain injury was assessed histologically at different times post HI. Convulsive seizures were observed in 65% of aging mice post-HI but not in control aging mice following either sham surgery or hypoxiaalone. These seizures typically occurred within hours of HI and behaviorally consisted of jumping, fast running, barrel-rolling, and/or falling (loss of the righting reflex) with limb spasms. No evident discharges during any convulsive seizures were seen on cortical-hippocampal EEG recordings. Seizure development was closely associated with acute mortality and severe brain injury on brain histological analysis. Intra-peritoneal injections of lorazepam and fosphenytoin suppressed seizures and improved survival but only when applied prior to seizure onset and not after. These findings together suggest that seizures are a major contributing factor to acute mortality in aging mice following severe brain ischemia and that early anticonvulsive treatment may prevent seizure genesis and improve overall outcomes.Ye