Predictor control for wave PDE / nonlinear ODE cascaded system with boundary value-dependent propagation speed

summary:This paper investigates predictor control for wave partial differential equation (PDE) and nonlinear ordinary differential equation (ODE) cascaded system with boundary value-dependent propagation speed. A predictor control is designed first. A two-step backstepping transformation and a new time variable are employed to derive a target system whose stability is established using Lyapunov arguments. The equivalence between stability of the target and the original system is provided using the invertibility of the backstepping transformations. Stability of the closed-loop system is established by Lyapunov arguments

Effect of Volume Loading Rate and C/N on Ship Domestic Sewage Treatment by Two Membrane Bioreactors

Design of ship sewage treatment systems that not only satisfy the use of small space on board but also meets International Maritime Organisation (IMO) latest emission standards is still a challenging problem for ship industry. This study provides a comparative disquisition between two different MBR reactors i.e, air-lift multilevel circulation membrane reactor (AMCMBR) and anaerobic/anoxic/aerobic membrane reactor (AOA-MBR) for domestic sewage treatment. The influence of pollutants volume loading rate (VLR) and C/N on effluent chemical oxygen demand (COD), ammonium nitrogen (NH4+-N) and TN for marine domestic sewage was analyzed. The results revealed that AMCMBR showed better removal efficiencies for COD and TN than AOA-MBR. The volume of AMCMBR was only half of the AOA-MBR. In addition, high average value of mixed liquor volatile suspended solids (MLVSS)/mixed liquid suspended solids (MLSS) (i.e. 0.75) of AMCMBR indicated high biomass and good pollutants removal achieved by this reactor. An interesting phenomenon was found in the study regarding Urease activity for the two reactors. Urease activity for AMCMBR in different working conditions all exceeded AOA-MBR and there exist no clear difference of NR activities between AMCMBR and AOA-MBR except for low C/N ratio (i.e. 6 and 4). This phenomenon proved that AMCMBR has a greater performance for treating ship domestic wastewater

Processing Efficiency, Simulation and Enzyme Activities Analysis of an Air-Lift Multilevel Circulation Membrane Bioreactor (AMCMBR) on Marine Domestic Sewage Treatment

The implementation of latest International Maritime Organization emission standard raised stringent requirements for marine domestic sewage discharge. In this study, an air-lift multilevel circulation membrane reactor (AMCMBR) was operated to analyze effects of various ecological factors on effluent of marine domestic sewage. Back-propagation (BP)-Artificial Neural Network (ANN) was used to simulate effect of each ecological factor on reactor performance. The activities of four enzymes were investigated to reveal microbial activities in reactor. Experimental results indicates that the Hydraulic Retention Time (HRT), Mixed Liquid Suspended Solids (MLSS) and pH value cannot be less than 4 h, 3000 mg/L and 6, respectively to meet the IMO emission standard for effluent COD. A small value of mean square error (0.00147) indicated that BP-ANN can well describe the relationship between operation parameters (influent COD, HRT, MLSS, and pH) and effluent COD. The order of relative importance was pH ≈ MLSS > HRT > influent COD. Polyphenol oxidase and urease can serve as indicating factors for reactor performance, whereas dehydrogenase and nitrate reductase showed less susceptible towards varied influent COD and MLSS

Learning biological neuronal networks with artificial neural networks: neural oscillations

First-principles-based modelings have been extremely successful in providing crucial insights and predictions for complex biological functions and phenomena. However, they can be hard to build and expensive to simulate for complex living systems. On the other hand, modern data-driven methods thrive at modeling many types of high-dimensional and noisy data. Still, the training and interpretation of these data-driven models remain challenging. Here, we combine the two types of methods to model stochastic neuronal network oscillations. Specifically, we develop a class of first-principles-based artificial neural networks to provide faithful surrogates to the high-dimensional, nonlinear oscillatory dynamics produced by neural circuits in the brain. Furthermore, when the training data set is enlarged within a range of parameter choices, the artificial neural networks become generalizable to these parameters, covering cases in distinctly different dynamical regimes. In all, our work opens a new avenue for modeling complex neuronal network dynamics with artificial neural networks.Comment: 18 pages, 8 figure

Model-driven CT reconstruction algorithm for nano-resolution X-ray phase contrast imaging

The low-density imaging performance of a zone plate based nano-resolution hard X-ray computed tomography (CT) system can be significantly improved by incorporating a grating-based Lau interferometer. Due to the diffraction, however, the acquired nano-resolution phase signal may suffer splitting problem, which impedes the direct reconstruction of phase contrast CT (nPCT) images. To overcome, a new model-driven nPCT image reconstruction algorithm is developed in this study. In it, the diffraction procedure is mathematically modeled into a matrix B, from which the projections without signal splitting can be generated invertedly. Furthermore, a penalized weighed least-square model with total variation (PWLS-TV) is employed to denoise these projections, from which nPCT images with high accuracy are directly reconstructed. Numerical and physical experiments demonstrate that this new algorithm is able to work with phase projections having any splitting distances. Results also reveal that nPCT images with higher signal-to-noise-ratio (SNR) would be reconstructed from projections with larger signal splittings. In conclusion, a novel model-driven nPCT image reconstruction algorithm with high accuracy and robustness is verified for the Lau interferometer based hard X-ray nano-resolution phase contrast imaging

Epidemiological features of tuberculosis infection in a rural prefecture of Japan from 2007 to 2018

This study aimed to investigate the epidemiological features of reported tuberculosis (TB) infections in a western prefecture (Nagasaki Prefecture) from 2007 to 2018, and to identify the high-risk group for TB infection. The characteristics of 12 years of reported TB infections from the Nagasaki Prefectural Informational Center of Infectious Diseases were summarized by median (interquartile range [IQR]) and proportion; the annual TB infections’ notification rate regarding sex/age was calculated accordingly. The diagnosis of TB infection was made according to clinic symptoms and laboratory examination. In total, 4364 TB infections were reported in 2007 and 2018, with a median age (IQR) of 74 (55–84) years. The majority of TB infections were male (52.6%, 2297/4364), > 65 years (65.8%, 2869/4364), and indigenous (98.1%, 4276/4364). Among active TB, 66.9% (1833/2740) had pulmonary TB, and 25.3% (694/2740) were diagnosed as extrapulmonary TB. The highest notification rate of TB infection was observed in the elderly male population (> 85 years). The annual notification rate of TB infections ranged between 19.4/and 34.0/100,000 for 12 years. The notification rates of TB infections were high in older people of both sexes, especially in men aged > 85. Therefore, appropriate interventions and health management are essential for TB control in (and with a focus on) the elderly population

Highly responsive ground state of PbTaSe2_2: structural phase transition and evolution of superconductivity under pressure

Transport and magnetic studies of PbTaSe$_2$ under pressure suggest existence of two superconducting phases with the low temperature phase boundary at $\sim 0.25$ GPa that is defined by a very sharp, first order, phase transition. The first order phase transition line can be followed via pressure dependent resistivity measurements, and is found to be near 0.12 GPa near room temperature. Transmission electron microscopy and x-ray diffraction at elevated temperatures confirm that this first order phase transition is structural and occurs at ambient pressure near $\sim 425$ K. The new, high temperature / high pressure phase has a similar crystal structure and slightly lower unit cell volume relative to the ambient pressure, room temperature structure. Based on first-principles calculations this structure is suggested to be obtained by shifting the Pb atoms from the $1a$ to $1e$ Wyckoff position without changing the positions of Ta and Se atoms. PbTaSe$_2$ has an exceptionally pressure sensitive, structural phase transition with $\Delta T_s/\Delta P \approx - 1700$ K/GPa near 4 K, this first order transition causes an $\sim 1$ K ($\sim 25 \%$) step - like decrease in $T_c$ as pressure is increased through 0.25 GPa

Surface passivation for highly active, selective, stable, and scalable CO2 electroreduction

Electrochemical conversion of CO2 to formic acid using Bismuth catalysts is one the most promising pathways for industrialization. However, it is still difficult to achieve high formic acid production at wide voltage intervals and industrial current densities because the Bi catalysts are often poisoned by oxygenated species. Herein, we report a Bi3S2 nanowire-ascorbic acid hybrid catalyst that simultaneously improves formic acid selectivity, activity, and stability at high applied voltages. Specifically, a more than 95% faraday efficiency was achieved for the formate formation over a wide potential range above 1.0 V and at ampere-level current densities. The observed excellent catalytic performance was attributable to a unique reconstruction mechanism to form more defective sites while the ascorbic acid layer further stabilized the defective sites by trapping the poisoning hydroxyl groups. When used in an all-solid-state reactor system, the newly developed catalyst achieved efficient production of pure formic acid over 120 hours at 50 mA cm–2 (200 mA cell current)