RISE-Based Integrated Motion Control of Autonomous Ground Vehicles With Asymptotic Prescribed Performance

This article investigates the integrated lane-keeping and roll control for autonomous ground vehicles (AGVs) considering the transient performance and system disturbances. The robust integral of the sign of error (RISE) control strategy is proposed to achieve the lane-keeping control purpose with rollover prevention, by guaranteeing the asymptotic stability of the closed-loop system, attenuating systematic disturbances, and maintaining the controlled states within the prescribed performance boundaries. Three contributions have been made in this article: 1) a new prescribed performance function (PPF) that does not require accurate initial errors is proposed to guarantee the tracking errors restricted within the predefined asymptotic boundaries; 2) a modified neural network (NN) estimator which requires fewer adaptively updated parameters is proposed to approximate the unknown vertical dynamics; and 3) the improved RISE control based on PPF is proposed to achieve the integrated control objective, which analytically guarantees both the controller continuity and closed-loop system asymptotic stability by integrating the signum error function. The overall system stability is proved with the Lyapunov function. The controller effectiveness and robustness are finally verified by comparative simulations using two representative driving maneuvers, based on the high-fidelity CarSim-Simulink simulation

Effect of human activated NRAS on replication of delNS1 H5N1 influenza virus in MDCK cells

<p>Abstract</p> <p>Background</p> <p>RAS, coded by <it>ras </it>proto-oncogenes, played an important role in signal transmission to regulate cell growth and differentiation. Host activation of RAS was significant for IFN-sensitive vaccinia virus (delE3L) or attenuate influenza virus in unallowable cells.</p> <p>Results</p> <p>Huamn <it>NRAS </it>gene was activated by mutating in codon 61. Then the activation of NRAS was detected by western blot in MDCK cells. The delNS1 H5N1 influenza virus with deletion of NS1 eIF4GI binding domain was weak multiplication in MDCK cells. And the replication of delNS1 virus and expression of IFN-beta and IRF-3 were detected by Real-time PCR in MDCK cells infected with delNS1 virus. It was found that the delNS1 virus had a significant increase in MDCK cells when the NRAS was activated, and yet, expression of IRF-3 and IFN-beta were restrained.</p> <p>Conclusions</p> <p>The study demonstrated that activated NRAS played an important part for delNS1 virus replication in MDCK cells. Activated NRAS might be down-regulating the expression of antiviral cellular factors in delNS1 virus infected cells.</p

Explaining the cosmic ray spectrum feature of Auger beyond the ankle with dip model plus the galactic propagation effect

The Auger Collaboration has recently published the energy spectrum of cosmic rays above 1 EeV, which exhibits interesting features. These spectrum features provide an opportunity to investigate the propagation of ultra-high-energy cosmic rays (UHECRs). In this study, we have developed a model that incorporates the dip model for UHECRs in the extragalactic propagation, while accounting for the suppression due to diffusion and interactions within the galaxy. Our model demonstrates excellent agreement with the energy spectrum measured by Auger and supports a spectral index of 2 for the diffusion coefficient in the galaxy starting from $5\times10^{18}$eV.Comment: 5 pages, 2 figure

One-shot ultraspectral imaging with reconfigurable metasurfaces

One-shot spectral imaging that can obtain spectral information from thousands of different points in space at one time has always been difficult to achieve. Its realization makes it possible to get spatial real-time dynamic spectral information, which is extremely important for both fundamental scientific research and various practical applications. In this study, a one-shot ultraspectral imaging device fitting thousands of micro-spectrometers (6336 pixels) on a chip no larger than 0.5 cm$^2$, is proposed and demonstrated. Exotic light modulation is achieved by using a unique reconfigurable metasurface supercell with 158400 metasurface units, which enables 6336 micro-spectrometers with dynamic image-adaptive performances to simultaneously guarantee the density of spectral pixels and the quality of spectral reconstruction. Additionally, by constructing a new algorithm based on compressive sensing, the snapshot device can reconstruct ultraspectral imaging information ($\Delta\lambda$/$\lambda$~0.001) covering a broad (300-nm-wide) visible spectrum with an ultra-high center-wavelength accuracy of 0.04-nm standard deviation and spectral resolution of 0.8 nm. This scheme of reconfigurable metasurfaces makes the device can be directly extended to almost any commercial camera with different spectral bands to seamlessly switch the information between image and spectral image, and will open up a new space for the application of spectral analysis combining with image recognition and intellisense

Estimating Uncertainty in Multimodal Foundation Models using Public Internet Data

Foundation models are trained on vast amounts of data at scale using self-supervised learning, enabling adaptation to a wide range of downstream tasks. At test time, these models exhibit zero-shot capabilities through which they can classify previously unseen (user-specified) categories. In this paper, we address the problem of quantifying uncertainty in these zero-shot predictions. We propose a heuristic approach for uncertainty estimation in zero-shot settings using conformal prediction with web data. Given a set of classes at test time, we conduct zero-shot classification with CLIP-style models using a prompt template, e.g., "an image of a ", and use the same template as a search query to source calibration data from the open web. Given a web-based calibration set, we apply conformal prediction with a novel conformity score that accounts for potential errors in retrieved web data. We evaluate the utility of our proposed method in Biomedical foundation models; our preliminary results show that web-based conformal prediction sets achieve the target coverage with satisfactory efficiency on a variety of biomedical datasets

lncRNA profiling to elucidate the metabolic mechanism of green tea extract on weight loss in mice

Purpose: To understand the effects of green tea extract on weight loss at the gene level using long non-coding RNA (lncRNA) expression profiles. Methods: lncRNA expression signatures in rats fed two different diets were determined by analyzing previously published gene expression profiles in Gene Expression Omnibus (GEO). The lncRNAs specific to rats in a particular dietary group were confirmed using an additional autonomous dataset. LncRNA expression profiles were compared to explore the underlying mechanisms of green tea extract on weight loss. Results: Three lncRNAs (Gm38399, F730035P03Rik, and 5033430I15Rik) that may be the targets of green tea and that may play crucial roles in the lipid-lowering effects of green tea were identified. Using functional annotation databases, two of the targets of two of the lncRNAs were identified as Nav1 and Atxn1. Conclusion: Based on annotation databases, green tea extract may affect metabolic processes in adipocytes by regulating the lncRNAs GM38399 and 5033430I15Rik that modulate their cis-regulatory target genes Nav1 and Atxn1, respectively. Nav1 and Atxn1 may then regulate trans-regulatory lncRNAs

Research on the mechanism of neutral-point voltage fluctuation and capacitor voltage balancing control strategy of three-phase three-level T-type inverter

In order to solve the neutral-point voltage fluctuation problem of three-phase threelevel T-type inverters (TPTLTIs), the unbalance characteristics of capacitor voltages under different switching states and the mechanism of neutral-point voltage fluctuation are revealed. Based on the mathematical model of a TPTLTI, a feed-forward voltage balancing control strategy of DC-link capacitor voltages error is proposed. The strategy generates a DC bias voltage using a capacitor voltage loop with a proportional integral (PI) controller. The proposed strategy can suppress the neutral-point voltage fluctuation effectively and improve the quality of output currents. The correctness of the theoretical analysis is verified through simulations. An experimental prototype of a TPTLTI based on Digital Signal Processor (DSP) is built. The feasibility and effectiveness of the proposed strategy is verified through experiment. The results from simulations and experiment match very well

An Efficient Process for Co-Production of γ-Aminobutyric Acid and Probiotic \u3ci\u3eBacillus subtilis\u3c/i\u3e Cells

This study was to establish an integrated process for the co-production of γ-aminobutyric acid (GABA) and live probiotics. Six probiotic bacteria were screened and Bacillus subtilis ATCC 6051 showed the highest GABA-producing capacity. The optimal temperature and initial pH value for GABA production in B. subtilis were found to be 30 °C and 8.0, respectively. A variety of carbon and nitrogen sources were tested, and potato starch and peptone were the preferred carbon and nitrogen sources for GABA production, respectively. The concentrations of carbon source, nitrogen source and substrate (sodium L-glutamate) were then optimized using the response surface methodology. The GABA titer and concentration of viable cells of B. subtilis reached 19.74 g/L and 6.0 × 108 cfu/mL at 120 h. The GABA titer represents the highest production of GABA in B. subtilis. This work thus demonstrates a highly efficient co-production process for GABA and probiotic B. subtilis cells