Combining statistical methods with dynamical insight to improve nonlinear estimation

Physical processes such as the weather are usually modelled using nonlinear dynamical systems. Statistical methods are found to be difficult to draw the dynamical information from the observations of nonlinear dynamics. This thesis is focusing on combining statistical methods with dynamical insight to improve the nonlinear estimate of the initial states, parameters and future states. In the perfect model scenario (PMS), method based on the Indistin-guishable States theory is introduced to produce initial conditions that are consistent with both observations and model dynamics. Our meth-ods are demonstrated to outperform the variational method, Four-dimensional Variational Assimilation, and the sequential method, En-semble Kalman Filter. Problem of parameter estimation of deterministic nonlinear models is considered within the perfect model scenario where the mathematical structure of the model equations are correct, but the true parameter values are unknown. Traditional methods like least squares are known to be not optimal as it base on the wrong assumption that the distribu-tion of forecast error is Gaussian IID. We introduce two approaches to address the shortcomings of traditional methods. The first approach forms the cost function based on probabilistic forecasting; the second approach focuses on the geometric properties of trajectories in short term while noting the global behaviour of the model in the long term. Both methods are tested on a variety of nonlinear models, the true parameter values are well identified. Outside perfect model scenario, to estimate the current state of the model one need to account the uncertainty from both observatiOnal noise and model inadequacy. Methods assuming the model is perfect are either inapplicable or unable to produce the optimal results. It is almost certain that no trajectory of the model is consistent with an infinite series of observations. There are pseudo-orbits, however, that are consistent with observations and these can be used to estimate the model states. Applying the Indistinguishable States Gradient De-scent algorithm with certain stopping criteria is introduced to find rel-evant pseudo-orbits. The difference between Weakly Constraint Four-dimensional Variational Assimilation (WC4DVAR) method and Indis-tinguishable States Gradient Descent method is discussed. By testing on two system-model pairs, our method is shown to produce more consistent results than the WC4DVAR method. Ensemble formed from the pseudo-orbit generated by Indistinguishable States Gradient Descent method is shown to outperform the Inverse Noise ensemble in estimating the current states. Outside perfect model scenario, we demonstrate that forecast with relevant adjustment can produce better forecast than ignoring the existence of model error and using the model directly to make fore-casts. Measurement based on probabilistic forecast skill is suggested to measure the predictability outside PMS

Laplace’s Demon and the Adventures of His Apprentices

The sensitive dependence on initial conditions (SDIC) associated with nonlinear models imposes limitations on the models’ predictive power. We draw attention to an additional limitation than has been underappreciated, namely, structural model error (SME). A model has SME if the model dynamics differ from the dynamics in the target system. If a nonlinear model has only the slightest SME, then its ability to generate decision-relevant predictions is compromised. Given a perfect model, we can take the effects of SDIC into account by substituting probabilistic predictions for point predictions. This route is foreclosed in the case of SME, which puts us in a worse epistemic situation than SDIC

N-Acetyl-Serotonin Protects HepG2 Cells from Oxidative Stress Injury Induced by Hydrogen Peroxide

Oxidative stress plays an important role in the pathogenesis of liver diseases. N-Acetyl-serotonin (NAS) has been reported to protect against oxidative damage, though the mechanisms by which NAS protects hepatocytes from oxidative stress remain unknown. To determine whether pretreatment with NAS could reduce hydrogen peroxide- (H2O2-) induced oxidative stress in HepG2 cells by inhibiting the mitochondrial apoptosis pathway, we investigated the H2O2-induced oxidative damage to HepG2 cells with or without NAS using MTT, Hoechst 33342, rhodamine 123, Terminal dUTP Nick End Labeling Assay (TUNEL), dihydrodichlorofluorescein (H2DCF), Annexin V and propidium iodide (PI) double staining, immunocytochemistry, and western blot. H2O2 produced dramatic injuries in HepG2 cells, represented by classical morphological changes of apoptosis, increased levels of malondialdehyde (MDA) and intracellular reactive oxygen species (ROS), decreased activity of superoxide dismutase (SOD), and increased activities of caspase-9 and caspase-3, release of cytochrome c (Cyt-C) and apoptosis-inducing factor (AIF) from mitochondria, and loss of membrane potential (ΔΨm). NAS significantly inhibited H2O2-induced changes, indicating that it protected against H2O2-induced oxidative damage by reducing MDA levels and increasing SOD activity and that it protected the HepG2 cells from apoptosis through regulating the mitochondrial apoptosis pathway, involving inhibition of mitochondrial hyperpolarization, release of mitochondrial apoptogenic factors, and caspase activity

A New Series of Small Molecular Weight Compounds Induce Read Through of All Three Types of Nonsense Mutations in the ATM Gene

Chemical-induced read through of premature stop codons might be exploited as a potential treatment strategy for genetic disorders caused by nonsense mutations. Despite the promise of this approach, only a few read-through compounds (RTCs) have been discovered to date. These include aminoglycosides (e.g., gentamicin and G418) and nonaminoglycosides (e.g., PTC124 and RTC13). The therapeutic benefits of these RTCs remain to be determined. In an effort to find new RTCs, we screened an additional ~36,000 small molecular weight compounds using a high-throughput screening (HTS) assay that we had previously developed and identified two novel RTCs, GJ071, and GJ072. The activity of these two compounds was confirmed in cells derived from ataxia telangiectasia (A-T) patients with three different types of nonsense mutation in the ATM gene. Both compounds showed activity comparable to stop codons (TGA, TAG, and TAA) PTC124 and RTC13. Early structure-activity relationship studies generated eight active analogs of GJ072. Most of those analogs were effective on all three stop codons. GJ071 and GJ072, and some of the GJ072 analogs, appeared to be well tolerated by A-T cells. We also identified another two active RTCs in the primary screen, RTC204 and RTC219, which share a key structural feature with GJ072 and its analogs

An Overview on IEEE 802.11bf: WLAN Sensing

With recent advancements, the wireless local area network (WLAN) or wireless fidelity (Wi-Fi) technology has been successfully utilized to realize sensing functionalities such as detection, localization, and recognition. However, the WLANs standards are developed mainly for the purpose of communication, and thus may not be able to meet the stringent requirements for emerging sensing applications. To resolve this issue, a new Task Group (TG), namely IEEE 802.11bf, has been established by the IEEE 802.11 working group, with the objective of creating a new amendment to the WLAN standard to meet advanced sensing requirements while minimizing the effect on communications. This paper provides a comprehensive overview on the up-to-date efforts in the IEEE 802.11bf TG. First, we introduce the definition of the 802.11bf amendment and its formation and standardization timeline. Next, we discuss the WLAN sensing use cases with the corresponding key performance indicator (KPI) requirements. After reviewing previous WLAN sensing research based on communication-oriented WLAN standards, we identify their limitations and underscore the practical need for the new sensing-oriented amendment in 802.11bf. Furthermore, we discuss the WLAN sensing framework and procedure used for measurement acquisition, by considering both sensing at sub-7GHz and directional multi-gigabit (DMG) sensing at 60 GHz, respectively, and address their shared features, similarities, and differences. In addition, we present various candidate technical features for IEEE 802.11bf, including waveform/sequence design, feedback types, as well as quantization and compression techniques. We also describe the methodologies and the channel modeling used by the IEEE 802.11bf TG for evaluation. Finally, we discuss the challenges and future research directions to motivate more research endeavors towards this field in details.Comment: 31 pages, 25 figures, this is a significant updated version of arXiv:2207.0485

Catalytic Hydrogen Evolution of NaBH4_4 Hydrolysis by Cobalt Nanoparticles Supported on Bagasse-Derived Porous Carbon

As a promising hydrogen storage material, sodium borohydride (NaBH4) exhibits superior stability in alkaline solutions and delivers 10.8 wt.% theoretical hydrogen storage capacity. Nevertheless, its hydrolysis reaction at room temperature must be activated and accelerated by adding an effective catalyst. In this study, we synthesize Co nanoparticles supported on bagasse-derived porous carbon (Co@xPC) for catalytic hydrolytic dehydrogenation of NaBH$_4$. According to the experimental results, Co nanoparticles with uniform particle size and high dispersion are successfully supported on porous carbon to achieve a Co@150PC catalyst. It exhibits particularly high activity of hydrogen generation with the optimal hydrogen production rate of 11086.4 mL$_{H2}$∙min$^{H2}$∙g$_{Co}$$^{H2}$ and low activation energy (E$_{a}$) of 31.25 kJ mol$^{H2}$. The calculation results based on density functional theory (DFT) indicate that the Co@xPC structure is conducive to the dissociation of [BH$_{4}$]$^{-}$, which effectively enhances the hydrolysis efficiency of NaBH$_4$. Moreover, Co@150PC presents an excellent durability, retaining 72.0% of the initial catalyst activity after 15 cycling tests. Moreover, we also explored the degradation mechanism of catalyst performance