Prescribed Performance Fuzzy Adaptive Output-Feedback Control for Nonlinear Stochastic Systems

A prescribed performance fuzzy adaptive output-feedback control approach is proposed for a class of single-input and single-output nonlinear stochastic systems with unmeasured states. Fuzzy logic systems are used to identify the unknown nonlinear system, and a fuzzy state observer is designed for estimating the unmeasured states. Based on the backstepping recursive design technique and the predefined performance technique, a new fuzzy adaptive output-feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded in probability and the tracking error remains an adjustable neighborhood of the origin with the prescribed performance bounds. A simulation example is provided to show the effectiveness of the proposed approach

Episodic X-ray Emission Accompanying the Activation of an Eruptive Prominence: Evidence of Episodic Magnetic Reconnection

We present an X-ray imaging and spectroscopic study of a partially occulted C7.7 flare on 2003 April 24 observed by RHESSI that accompanied a prominence eruption observed by TRACE. (1) The activation and rise of the prominence occurs during the preheating phase of the flare. The initial X-ray emission appears as a single coronal source at one leg of the prominence and it then splits into a double source. Such a source splitting happens three times, each coinciding with an increased X-ray flux and plasma temperature, suggestive of fast reconnection in a localized current sheet and an enhanced energy release rate. In the late stage of this phase, the prominence displays a helical structure. These observations are consistent with the tether-cutting and/or kink instability model for triggering solar eruptions. (2) The eruption of the prominence takes place during the flare impulsive phase. Since then, there appear signatures predicted by the classical CSHKP model of two-ribbon flares occurring in a vertical current sheet trailing an eruption. These signatures include an EUV cusp and current-sheet-like feature (or ridge) above it. There is also X-ray emission along the EUV ridge both below and above the cusp, which in both regions appears closer to the cusp at higher energies in the thermal regime. This trend is reversed in the nonthermal regime. (3) Spectral analysis indicates thermal X-rays from all sources throughout the flare, while during the impulsive phase there is additional nonthermal emission which primarily comes from the coronal source below the cusp. This source also has a lower temperature, a higher emission measure, and a much harder nonthermal spectrum than the upper sources.Comment: 8 pages, 5 figures, submitted to Ap

Super-resolution imaging through a multimode fiber: the physical upsampling of speckle-driven

Following recent advancements in multimode fiber (MMF), miniaturization of imaging endoscopes has proven crucial for minimally invasive surgery in vivo. Recent progress enabled by super-resolution imaging methods with a data-driven deep learning (DL) framework has balanced the relationship between the core size and resolution. However, most of the DL approaches lack attention to the physical properties of the speckle, which is crucial for reconciling the relationship between the magnification of super-resolution imaging and the quality of reconstruction quality. In the paper, we find that the interferometric process of speckle formation is an essential basis for creating DL models with super-resolution imaging. It physically realizes the upsampling of low-resolution (LR) images and enhances the perceptual capabilities of the models. The finding experimentally validates the role played by the physical upsampling of speckle-driven, effectively complementing the lack of information in data-driven. Experimentally, we break the restriction of the poor reconstruction quality at great magnification by inputting the same size of the speckle with the size of the high-resolution (HR) image to the model. The guidance of our research for endoscopic imaging may accelerate the further development of minimally invasive surgery

Bi-Drop: Enhancing Fine-tuning Generalization via Synchronous sub-net Estimation and Optimization

Pretrained language models have achieved remarkable success in natural language understanding. However, fine-tuning pretrained models on limited training data tends to overfit and thus diminish performance. This paper presents Bi-Drop, a fine-tuning strategy that selectively updates model parameters using gradients from various sub-nets dynamically generated by dropout. The sub-net estimation of Bi-Drop is performed in an in-batch manner, so it overcomes the problem of hysteresis in sub-net updating, which is possessed by previous methods that perform asynchronous sub-net estimation. Also, Bi-Drop needs only one mini-batch to estimate the sub-net so it achieves higher utility of training data. Experiments on the GLUE benchmark demonstrate that Bi-Drop consistently outperforms previous fine-tuning methods. Furthermore, empirical results also show that Bi-Drop exhibits excellent generalization ability and robustness for domain transfer, data imbalance, and low-resource scenarios.Comment: EMNLP 2023 Findings. Camera-ready version. Co-first authors with equal contribution

Driver-centered pervasive application for heart rate measurement

People spend a significant amount of time daily in the driving seat and some health complexity is possible to happen like heart-related problems, and stroke. Driver’s health conditions may also be attributed to fatigue, drowsiness, or stress levels when driving on the road. Drivers’ health is important to make sure that they are vigilant when they are driving on the road. A driver-centered pervasive application is proposed to monitor a driver’s heart rate while driving. The input will be acquired from the interaction between the driver and embedded sensors at the steering wheel, which is tied to a Bluetooth link with an Android smartphone. The driver can view his historical data easily in tabular or graph form with selected filters using the application since the sensor data are transferred to a real-time database for storage and analysis. The application is coupled with the tool to demonstrate an opportunity as an aftermarket service for vehicles that are not equipped with this technology

Myeloid-Specific Deficiency of Pregnane X Receptor Decreases Atherosclerosis in LDL Receptor-Deficient Mice

Abstract The pregnane X receptor (PXR) is a nuclear receptor that can be activated by numerous drugs and xenobiotic chemicals. PXR thereby functions as a xenobiotic sensor to coordinately regulate host responses to xenobiotics by transcriptionally regulating many genes involved in xenobiotic metabolism. We have previously reported that PXR has pro-atherogenic effects in animal models, but how PXR contributes to atherosclerosis development in different tissues or cell types remains elusive. In this study, we generated an LDL receptor-deficient mouse model with myeloid-specific PXR deficiency (PXRΔMyeLDLR−/−) to elucidate the role of macrophage PXR signaling in atherogenesis. The myeloid PXR deficiency did not affect metabolic phenotypes and plasma lipid profiles, but PXRΔMyeLDLR−/− mice had significantly decreased atherosclerosis at both aortic root and brachiocephalic arteries compared with control littermates. Interestingly, the PXR deletion did not affect macrophage adhesion and migration properties, but reduced lipid accumulation and foam cell formation in the macrophages. PXR deficiency also led to decreased expression of the scavenger receptor CD36 and impaired lipid uptake in macrophages of the PXRΔMyeLDLR−/− mice. Further, RNA-Seq analysis indicated that treatment with a prototypical PXR ligand affects the expression of many atherosclerosis-related genes in macrophages in vitro. These findings reveal a pivotal role of myeloid PXR signaling in atherosclerosis development and suggest that PXR may be a potential therapeutic target in atherosclerosis management

Woodpecker: Hallucination Correction for Multimodal Large Language Models

Hallucination is a big shadow hanging over the rapidly evolving Multimodal Large Language Models (MLLMs), referring to the phenomenon that the generated text is inconsistent with the image content. In order to mitigate hallucinations, existing studies mainly resort to an instruction-tuning manner that requires retraining the models with specific data. In this paper, we pave a different way, introducing a training-free method named Woodpecker. Like a woodpecker heals trees, it picks out and corrects hallucinations from the generated text. Concretely, Woodpecker consists of five stages: key concept extraction, question formulation, visual knowledge validation, visual claim generation, and hallucination correction. Implemented in a post-remedy manner, Woodpecker can easily serve different MLLMs, while being interpretable by accessing intermediate outputs of the five stages. We evaluate Woodpecker both quantitatively and qualitatively and show the huge potential of this new paradigm. On the POPE benchmark, our method obtains a 30.66%/24.33% improvement in accuracy over the baseline MiniGPT-4/mPLUG-Owl. The source code is released at https://github.com/BradyFU/Woodpecker.Comment: 16 pages, 7 figures. Code Website: https://github.com/BradyFU/Woodpecke

A Systematic Analysis of Fe II Emission in Quasars: Evidence for Inflow to the Central Black Hole

Broad Fe II emission is a prominent feature of the optical and ultraviolet spectra of quasars. We report on a systematical investigation of optical Fe II emission in a large sample of 4037 z < 0.8 quasars selected from the Sloan Digital Sky Survey. We have developed and tested a detailed line-fitting technique, taking into account the complex continuum and narrow and broad emission-line spectrum. Our primary goal is to quantify the velocity broadening and velocity shift of the Fe II spectrum in order to constrain the location of the Fe II-emitting region and its relation to the broad-line region. We find that the majority of quasars show Fe II emission that is redshifted, typically by ~ 400 km/s but up to 2000 km/s, with respect to the systemic velocity of the narrow-line region or of the conventional broad-line region as traced by the Hbeta line. Moreover, the line width of Fe II is significantly narrower than that of the broad component of Hbeta. We show that the magnitude of the Fe II redshift correlates inversely with the Eddington ratio, and that there is a tendency for sources with redshifted Fe II emission to show red asymmetry in the Hbeta line. These characteristics strongly suggest that Fe II originates from a location different from, and most likely exterior to, the region that produces most of Hbeta. The Fe II-emitting zone traces a portion of the broad-line region of intermediate velocities whose dynamics may be dominated by infall.Comment: 20 pages, 14 figures, accepted for publication in Ap