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In this paper, we present a coded aperture snapshot linear-Stokes imaging spectropolarimeter (CASSIS) based on a combination of coded aperture spectral imager and a division-of-focal-plane polarization camera. The CASSIS achieves aperture coding with a digital micromirror device (DMD) first, and then encodes polarization state using the polarization camera. Finally, the camera gets the coded polarization spatio-spectral image at a single snapshot. Linear-Stokes spectral images are estimated with sparsity-constrained optimization from the acquired image. The principle and feasibility are validated with simulations. It is noted that a modest peak-signal-to-noise ratio (PSNR) is recovered with a single snapshot, and higher PSNR is obtained with multiple snapshots.

Single metal-organic coordination polymers have limited functions as precursors for porous carbon electrode materials. The construction of bimetallic organic coordination polymers can effectively utilize the advantages of each single metal-organic coordination polymer to improve the performance of the derived carbon materials. Herein, High performance nitrogen-doped porous carbon (BCFe–Ni) have been produced by directly carbonizing bimetallic organic coordination polymers formed by 4,4′-bipyridine (BPD) reaction with FeCl3 and NiCl2. The BCFe–Ni exhibits high nitrogen content (12.66 at%), large specific surface area (1049.51 m2 g−1) and hierarchical porous structure, which contributes to an excellent gravimetric specific gravity of 320.5 F g−1 and 108% of specific capacitance retention after 10000 cycles. The BCFe–Ni assembled symmetrical supercapacitor shows an energy density of 18.3 W h kg−1 at a power density of 350 W kg−1. It is expected that the as-prepared N-doped porous carbon derived from bimetallic-organic coordination polymer is a promising electrode material for high performance energy storage devices. Keywords: Bimetallic-organic coordination polymers, N-doped porous carbon, High specific surface area, Supercapacitors

Improving effector activity of antigen specific T cells is a major goal in cancer immunotherapy. Despite the identification of several effector T cell (TEFF)-driving transcription factors (TF), the transcriptional coordination of TEFF biology remains poorly understood. We developed an in vivo T cell CRISPR screening platform and identified a novel mechanism restraining TEFF biology through the ETS family TF, Fli1. Genetic deletion of Fli1 enhanced TEFF responses without compromising memory or exhaustion precursors. Fli1 restrained TEFF lineage differentiation by binding to cis-regulatory elements of effector-associated genes. Loss of Fli1 increased chromatin accessibility at ETS:RUNX motifs allowing more efficient Runx3-driven TEFF biology. CD8 T cells lacking Fli1 provided substantially better protection against multiple infections and tumors. These data indicate that Fli1 safeguards the developing CD8 T cell transcriptional landscape from excessive ETS:RUNX-driven TEFF cell differentiation. Moreover, genetic deletion of Fli1 improves TEFF differentiation and protective immunity in infections and cancer.

Lithium-ion battery, as the mainstream power source of electric vehicles, suffers the performance degradation in the long-term vehicular usage. Battery health monitoring is quite an important task of the battery management system. This paper presents a novel method of online estimating the battery state of health (SOH) based on the evolution of the model error during the battery aging process. The monitoring model is established by using the test data of fresh batteries. During the process of battery aging, the model precision gradually declines and there is an implicit correlation between the aging degree and the distribution of model error. The model error spectrum (MES) is established based on the kurtosis and skewness of the model error statistics. It is found that there is an exponential relation between battery SOH and the MES. Based on the above work, the online SOH estimation is proposed by obtaining the MES within the historical data in a pre-set time window. The experiments are used to evaluate the presented method. The results indicate that the precise estimation results of battery SOH can be obtained with the error less than 1.07%. It is expected that the presented method is useful in online health monitoring and prognosis applications of the lithium-ion batteries in electric vehicles.

Driving cycle development is crucial in electric vehicles (EVs) power management design and evaluation. In this study, a Markov chain-based method is proposed to develop the typical driving cycle for electric vehicle application in Shenyang, China. The presented study is composed by three steps: (1) the driving data is divided by states according to two dimensional factors, namely the speed and the acceleration; (2) the state transition matrix and Markov transfer probability are calculated; (3) the driving cycle is established based on the Markov state using Monte Carlo simulation. Based on the above effort, ten candidate cycles satisfying the time length between 500 s and 3000 s are constructed, among which the typical driving cycle is determined by the performance value (PV) and sum square difference (SSD). A blended power management of hybrid electric vehicle has been applied on the established driving cycle, the test results indicate that the presented method can produce a very representative driving cycle.

Numerous biologics are currently licensed for the treatment of psoriasis, including new drugs targeting interleukin-17 (IL-17) and interleukin-23 (IL-23). This meta-analysis evaluated the short-term (12-16 weeks) efficacy and safety of biologics targeting IL-17 and IL-23 in the treatment of moderate-to-severe plaque psoriasis. Twenty-one randomized clinical trials met the defined inclusion criteria. Our results showed that Ixekizumab (160 mg wk0 + 80 mg q2w) had the greatest probability of achieving both PASI 75 (RR 21.32, 95% CI 15.48-29.36, P < 0.00001) and PASI 90 response (RR 59.76, 95% CI 32.41-110.19, P < 0.00001) at the primary endpoint times, followed by Ustekinumab and Secukinumab. Regarding the safety profile, Tildtakizumab (200 mg, q4w) was safest (RR 0.88, 95% CI 0.78-0.99, P = 0.04), while Ixekizumab (160 mg wk0 + 80 mg q2w) showed highest risk for one or more AE (RR 1.26, 95% CI 1.15-1.38, P < 0.00001). However, there was no significant difference between the two biologics regarding one or more SAEs. Comparing to the biologics targeting IL-23, the pooled effect size favored the biological agents targeting IL-17 in terms of the PASI 75 (PASI 75: RR 17.28, 95% CI 14.51-20.58, P < 0.00001) and PASI 90 (RR 37.19, 95% CI 26.91-51.41, P < 0.00001). The rate of overall AEs was significantly higher (P < 0.00001) in biologics targeting the IL-17 (RR 1.18, 95% CI 1.12-1.24, P < 0.00001) compared to biologics targeting IL-23 (RR 0.97, 95% CI 0.91-1.04, P = 0.44), and with respect to one or more SAEs, no difference was seen between biologics targeting IL-17 and IL-23. This meta-analysis found that Ixekizumab was the most effective short-term treatment, but was ranked as the most risk therapeutic choice among the biologics involved in this study, while Tildtakizumab was the best alternative in the case of safety. Furthermore, it demonstrated that biologics inhibiting IL-17 were superior to biologics targeting IL-23 in terms of the efficacy, but posed higher risk at the same time. This study might help the clinicians and guideline developers to choose the optimal one among these biologics for the treatment of moderate-to-severe plaque psoriasis.

During the calibration of the system matrix of a Stokes polarimeter using reference polarization states (RPSs) and pseudo-inversion estimation method, the measurement intensities are usually noised by the signal-independent additive Gaussian noise or signal-dependent Poisson shot noise, the precision of the estimated system matrix is degraded. In this paper, we present a paradigm for selecting RPSs to improve the precision of the estimated system matrix in the presence of both types of noise. The analytical solution of the precision of the system matrix estimated with the RPSs are derived. Experimental measurements from a general Stokes polarimeter show that accurate system matrix is estimated with the optimal RPSs, which are generated using two rotating quarter-wave plates. The advantage of using optimal RPSs is a reduction in measurement time with high calibration precision.

The impact of SOC and temperature on external short circuit (ESC) faults characteristics of lithium-ion batteries, including the current and voltage variation and temperature increase, are analyzed. A fractional-order model (FOM) and a first-order RC model are both employed to describe the electrical behavior of the battery cells with the ESC fault. While the model parameters are identified by the genetic algorithm (GA). A comparison study is made on the prediction accuracy for the two models. An effective classification method based on a random forests (RF) model is proposed to recognize the electrolyte leakage behavior that occurs during the ESC fault experiments. Based on the above efforts, the three steps model-based diagnosis algorithm for identifying the ESC fault and even electrolyte leakage of the battery in real-time is proposed. Two indicators of the root mean square error (RMSE) of battery predicting voltage are applied to diagnose for the ESC fault only and ESC-leakage merged fault. The result of the leakage condition is obtained by a pre-trained RF classifier to confirm the leakage detection result based on the RMSE indicator. Several cases are verified that all the ESC cells can be diagnosed efficiently.

Persistent viral infections and tumors drive development of exhausted T (TEX) cells. In these settings, TEX cells establish an important host-pathogen or host-tumor stalemate. However, TEX cells erode over time, leading to loss of pathogen or cancer containment. We identified microRNA (miR)-155 as a key regulator of sustained TEX cell responses during chronic lymphocytic choriomeningitis virus (LCMV) infection. Genetic deficiency of miR-155 ablated CD8 T cell responses during chronic infection. Conversely, enhanced miR-155 expression promoted expansion and long-term persistence of TEX cells. However, rather than strictly antagonizing exhaustion, miR-155 promoted a terminal TEX cell subset. Transcriptional profiling identified coordinated control of cell signaling and transcription factor pathways, including the key AP-1 family member Fosl2. Overexpression of Fosl2 reversed the miR-155 effects, identifying a link between miR-155 and the AP-1 transcriptional program in regulating TEX cells. Thus, we identify a mechanism of miR-155 regulation of TEX cells and a key role for Fosl2 in T cell exhaustion. During persistent viral infections, exhausted T cells (TEX) erode quantitatively and qualitatively and therefore fail to provide protection. Stelekati et al. identified microRNA (miR)-155 as a key molecule that can enhance and sustain TEX responses long-term during chronic viral infection.

We experimentally demonstrate 6.4 Tb/s wavelength division multiplexed (WDM) direct-detection transmission based on Nyquist twin-SSB modulation over 25 km SSMF with bit error rates (BERs) below the 20% hard-decision forward error correction (HD-FEC) threshold of 1.5 × 10−2. The two sidebands of each channel are separately detected using Kramers–Kronig receiver without MIMO equalization. We also carry out numerical simulations to evaluate the system robustness against I/Q amplitude imbalance, I/Q phase deviation and the extinction ratio of modulator, respectively. Furthermore, we show in simulation that the requirement of steep edge optical filter can be relaxed if multi-input–multi-output (MIMO) equalization between the two sidebands is used.

Carbon Nanotube assemblies are currently of considerable interest for their properties of high-packing-density and aligned configurations, which offer a promising route to achieve higher strength and conductivity in macroscopic materials. While most researches have focused on their mechanical and electrical properties, recently, their light absorption and thermal conductivity have attracted more and more attention. This work introduces a novel freestanding optoacoustic transducer using continuous multilayered carbon nanotube yarns, gold nanoparticles and elastomeric polymer, which can be used for efficient conversion from laser energy to acoustic power and generating high acoustic pressure (~33.6 MPa) without focusing. The calculated energy conversion efficiency is as high as 2.74 × 10−2. Such excellent performances could be attributed to its freestanding structure and the enhanced optical absorption due to localized surface plasmon resonance (LSPR) caused by gold nanoparticles. The laser-generated ultrasound has been experimentally demonstrated to be capable of manipulating micro particles (50 µm) in a transparent channel.

The effect of the ratio of two retarders for the demodulation in the intensity modulation spectropolarimeter is proposed. The five-channel autocorrelation function is introduced for the first time, its forming conditions and the principle of spectrum reconstruction are analyzed. From the analysis of the spectropolarimeter based on the interference spectrometer, we can conclude that the spectral resolution of some Stokes parameters reconstructed by the five-channel interferogram is improved compared with the seven-channel interferogram. The simulation experiment of spectrum recovery of five-channel autocorrelation function is carried out. The simulation results are in good agreement with the theory, and the results show that the scheme of the five-channel is feasible, which provides a good theoretical basis and reference for the optimization design of the spectropolarimeter.

External short circuit (ESC) is a severe fault that can cause the large current and high temperature of lithium-ion batteries (LiBs) immediately. Temperature rise prediction is crucial for LiB safety management in an all-climate electric vehicles application because many disastrous consequences are caused by high temperature. This study mainly investigates the ESC-caused temperature rise characteristics of LiB, and proposes an online prediction approach of the maximum temperature rise. Three original contributions are made: (1) Abusing tests of LiBs under ESC are conducted at varying ambient temperatures, and the influences of battery state of charge (SOC) and ambient temperature on the maximum temperature rise are revealed. (2) Characteristics of temperature rises are analysed, therein finding that the heat generation of LiBs caused by ESC presents two modes: Joule heat-dominant mode and reaction heat/Joule heat blended mode; leakage is an external manifestation of the latter. (3) Two heat generation modes are proved to be linearly separable at temperature rise discharge capacity plane, and then a two-step prediction approach of maximum temperature rise is proposed based on support vector machine. Finally, the presented approach is validated by the experimental data. The maximum temperature rise can be predicted up to 22.3 s ahead of time and very precise prediction results are obtained, where the mean prediction error for the eight test cells is 3.05%.

Channeled spectropolarimetry is a snapshot scheme for the full polarization spectra measurement. It has the advantages of static, compact, lightweight, and easy to implement. However, while the broadband polarization spectra can be precisely reconstructed using the regular methods, such as the method based on the Fourier transform, the reconstruction of narrowband polarization spectra always suffers from errors caused by the crosstalk among channels in the optical path difference domain. We present an efficient narrowband full polarization spectra reconstruction method for channeled spectropolarimetry. The line shape of the intensity spectrum is estimated by the envelop curve of the measured high frequency modulated spectrum. The full polarization spectra can be reconstructed by the least-square method under the assumption that polarization states change slowly with wavelength for narrowband polarization spectra. The feasibility of the reconstruction method has been verified by the simulation and experimental results.

Using a typical driving cycle to implement and evaluate the established control strategy is quite essential in the investigation of electric vehicles (EVs) power management issue. How to build a representative driving cycle remains a challenge due to the complex urban driving conditions. In this paper, the principal component analysis (PCA) and k-means cluster are employed to develop the driving cycle with case of Shenyang, China. First of all, a large amount of road conditions test data are collected, which are made up of a series of data including driving time and the instantaneous velocity. On top of that, the PCA is applied to extract the main components of overall road information and the K-means cluster is used to select representative kinematic fragments. Several most representative fragments are chosen to form the driving cycle. At last, the proposed driving cycle is simulated and verified. The result shows that the proposed driving cycle can well match to overall road information.

Accurate state of charge estimation of lithium-ion battery is directly related to the safe operation of electric vehicles and also an indispensable function of the battery management system. Four aspects of efforts are made to improve the estimation accuracy. First, for overcoming the drawbacks of equivalent circuit model and electrochemical model, the fractional order impedance model is built via electrochemical impedance spectroscopy data and the fractional element is used to describe the polarization effect in a simple and meaningful way. Second, the discrete state-space equations of the impedance model are inferred by Grunwald-Letnikov definition and parameters of the model including the order of the fractional element are identified together by genetic algorithm (GA) and the experiment data of the dynamic driving cycles. Third, the fractional order unscented Kalman filter technique is presented and the ‘short memory’ technique is employed to improve the computation efficiency of fractional operator. Lastly, experimental validation is implemented to verify the effectiveness of the proposed approach and results show that the SoC estimation accuracy can be improved by the proposed model and estimation method. The estimation error can be controlled within the range of 3%.

In a static wind imaging Michelson interferometer (SWIMI) developed by us, two-arm glasses are used to achieve the achromatic thermally compensation. The arm glass is cemented with the beam splitter. The tilt of the arm glass would cause a change to the optical path difference (OPD), thereby reducing the visibility of the interferogram and introducing phase error to the SWIMI system, which eventually responsible for errors in the inversion of temperature and wind velocity. In this paper, we present the principle of static wind imaging interferometer and derivate the variation of OPD caused by the two-dimensional tilt of arm glass in detail. By considering a rectangle incident beam, we analyze the effect of arm glass tilt on wind speed and temperature inversion. The results show that in order to realize the wind velocity error less than 3 m/s, the temperature error less than 3 K, and the instrument visibility greater than 0.8, the two-dimensional tilted angle of arm glass should be less than 1”. The tolerance of tilted angle can expand by adjusting the refractive index of the medium on both two sides of the arm glass or by adjusting the reflector mirror of the interferometer precisely. The results would be helpful for the cement of arm glass, beam splitter of SWIMI, and provide a reference for the design of a field-widened wind imaging interferometer.

External short circuit (ESC) fault, which can cause large current and high temperature, is one of the main reasons for battery failure. Its analysis and diagnosis remains a challenging task due to complex electro-thermal characteristics of batteries under ESCs. In this paper, ESC experiments at various temperatures are conducted to investigate the impact of temperature on battery electro-thermal behaviors. Based on the analysis of the experimental data, heat generation inside a battery caused by ESC-induced high current and side reactions is modeled. The heat distribution and diffusion are also modeled by considering battery's internal jellyroll structure. The combination of the heat generation, distribution and diffusion models forms a novel electro-thermal coupling model, which is used to predict the complex thermal and electrical properties of a battery under ESCs. The presented model is simulated and verified by the test data. The maximum root mean square error of ESC current prediction is less than 1.73A and the maximum errors of the internal temperatures and the surface temperatures are only 1.771% and 3.915%, respectively. These results verify the effectivceness of the presented model. It is expected that the presented model is useful for safety analysis, temperature prediction and fault diagnosis applications of the lithium-ion batteries under ESC.

Background Psoriasis is a T cell–mediated autoimmune skin disease. Accumulating evidence has demonstrated that co-inhibitory receptors (CIRs) play a vital role in regulating T cell–mediated immune response, especially in neoplasm and autoimmunity. However, the immuno-function of CIRs in the development of psoriasis remains unclear. Objective We investigated the expression of CIRs on the circulating T lymphocytes of psoriasis patients before and after anti–tumor necrosis factor-α (TNF-α) therapy. Methods We enrolled 17 patients with moderate-to-severe plaque psoriasis, 17 patients with mild plaque psoriasis, and 18 healthy controls in this study. Fourteen of the moderate-to-severe psoriasis patients were treated with infliximab, a monoclonal antibody against TNF-α. Peripheral blood was collected, and peripheral blood mononuclear cells were extracted. The proportion of T cell subsets along with their expression of CIRs, namely T cell immunoreceptor with Ig and ITIM domains (TIGIT), lymphocyte activating gene 3 (LAG-3), cytotoxic T–lymphocyte associated protein 4 (CTLA-4), B and T lymphocyte–associated protein (BTLA), endothelial protein C receptor (PROCR), podoplanin (PDPN), programmed cell death 1 (PD-1), and T cell immunoglobulin mucin family containing molecule 3 (TIM-3), were determined by flow cytometric assay. Results The moderate-to-severe plaque psoriasis patients had less circulating Tregs, which increased after infliximab treatment. They also had decreased TIGIT, LAG-3 but increased PDPN expression on peripheral CD4+ T cells. Infliximab enhanced TIGIT, LAG-3, CTLA-4 but reduced PROCR expression on circulating CD4+ T cells. Remarkably, both the frequency of circulating Tregs and the expression level of TIGIT on CD4+ T cells at baseline (pre-treatment) negatively correlated with the extent of PASI score reduction benefited from infliximab therapy. Conclusion Anti–TNF-α therapy increased the frequency of Tregs and TIGIT, LAG-3, CTLA-4 expression but reduced PROCR expression on circulating CD4+ T cells in psoriasis patients. The baseline proportion of Tregs and the expression level of TIGIT on circulating CD4+ T cells might serve as predictive markers for the degree of disease remission benefited from infliximab treatment.

An acylative Suzuki coupling of activated amides with aryl boronic acids has been reported via palladium-catalyzed C N bond cleavage. This protocol demonstrate amides can be activated by an atom-economic and cheap succinimide, which can be efficiently utilized to synthesize broad array of diaryl ketones in moderate to good yields.

Summary MicroRNAs play an important role in T cell responses. However, how microRNAs regulate CD8 T cell memory remains poorly defined. Here, we found that miR-150 negatively regulates CD8 T cell memory in vivo. Genetic deletion of miR-150 disrupted the balance between memory precursor and terminal effector CD8 T cells following acute viral infection. Moreover, miR-150-deficient memory CD8 T cells were more protective upon rechallenge. A key circuit whereby miR-150 repressed memory CD8 T cell development through the transcription factor c-Myb was identified. Without miR-150, c-Myb was upregulated and anti-apoptotic targets of c-Myb, such as Bcl-2 and Bcl-xL, were also increased, suggesting a miR-150-c-Myb survival circuit during memory CD8 T cell development. Indeed, overexpression of non-repressible c-Myb rescued the memory CD8 T cell defects caused by overexpression of miR-150. Overall, these results identify a key role for miR-150 in memory CD8 T cells through a c-Myb-controlled enhanced survival circuit.

Predictive energy management could be implemented in real-time with a short period of future driving cycle prediction. However, the completely precise prediction of the future driving cycle remains quite difficult. Two areas of effort have been explored in this study. The first is the implementation of a dynamic-neighborhood particle swarm optimization algorithm in the local optimal energy management strategy of plug-in hybrid electric vehicles based on data from the prediction of the future driving cycle. Second, the influence of an imprecise driving cycle prediction is considered, and then an online correction algorithm is proposed based on the backup control strategy and a fuzzy logic controller. In addition to these efforts, a predictive energy management strategy with an online correction algorithm is finally proposed. Compared with the optimal heuristic method, the presented energy management strategy could reduce the energy by up to 9.7% if the prediction of the future driving cycle is precise. For the situation of imprecise prediction, the online correction algorithm could reduce the deviation from the actual optimal policy by up to 32.39%.

This study investigates the external short circuit (ESC) fault characteristics of lithium-ion battery experimentally. An experiment platform is established and the ESC tests are implemented on ten 18650-type lithium cells considering different state-of-charges (SOCs). Based on the experiment results, several efforts have been made. (1) The ESC process can be divided into two periods and the electrical and thermal behaviors within these two periods are analyzed. (2) A modified first-order RC model is employed to simulate the electrical behavior of the lithium cell in the ESC fault process. The model parameters are re-identified by a dynamic-neighborhood particle swarm optimization algorithm. (3) A two-layer model-based ESC fault diagnosis algorithm is proposed. The first layer conducts preliminary fault detection and the second layer gives a precise model-based diagnosis. Four new cells are short-circuited to evaluate the proposed algorithm. It shows that the ESC fault can be diagnosed within 5 s, the error between the model and measured data is less than 0.36 V. The effectiveness of the fault diagnosis algorithm is not sensitive to the precision of battery SOC. The proposed algorithm can still make the correct diagnosis even if there is 10% error in SOC estimation.

While CuxO-CeO2 catalysts have a superb catalytic activity in preferential oxidation of CO, the reduction of CuxO to metallic Cu is inevitable on the surface due to the presence of H2-rich reaction atmosphere during catalysis, resulting in loss of active species and decreased activity. This work synthesized the CuO/CeO2 catalysts by the hydrothermal method, which consist of highly dispersed CuxO species, CuxO nanoclusters at the Cu-[Ox]-Ce interface, and bulk CuxO on the surface of catalysts. It is found that the highly dispersed CuxO clusters is responsible for low-temperature activity, and the CuxO clusters at the Cu-[Ox]-Ce interface play an important role at high temperature. After three cycle tests, the spent-10CuO/CeO2 catalyst is shown to be on-site regenerated during cooling process due to the synergy between copper and cerium species as well as strong interaction between the support and reactant molecules with fully accessible H2. The CeO2 suffers dynamic transformation during the cooling process when the copper and cerium species interact with reactant molecules. Understanding such dynamic process can help to reveal the evolution of the catalyst in the reaction atmosphere.

Energy management strategy (EMS) plays an important role in improving energy economy of plug-in hybrid electric vehicles (PHEVs). The frequently fluctuations of electricity and oil prices have significant impacts on EMS optimization. In this study, the influence law of the varying prices on the optimal control policy is revealed. The statistical analysis of electricity and fuel prices for typical cities in China is proposed as a case study, and then a varying prices-conscious EMS for PHEVs is developed. The presented control strategy is optimized based on the simulated annealing particle swarm optimization (SA-PSO) algorithm. Taking into account the above efforts, the price influence surfaces (PIS) are proposed and a PIS-based adaptive EMS is finally established. The presented control strategy can achieve better energy economy under real-world driving condition than traditional EMS that doesn't concern the impacts of price variations. The results indicate that the energy cost of PHEV can be further reduced by up to 9.88% under certain driving situations.

We demonstrated a novel strategy to prepare nitrogen-doped interpenetrating porous carbon/graphene (NIPCG) networks based on interpenetrating poly(o-phenylenediamine)/N-doped graphene networks. The as-prepared NIPCG shows both high nitrogen content of 13.1 at.% and density of 1.13 g cm−3, and displays ultrahigh specific gravimetric and volumetric capacitances of 673 F g−1 and 760 F cm−3, respectively. Furthermore, the interpenetrating networks structure can afford rapid electron transport, and thus exhibiting excellent conductivity and good cycling stability. In addition, NIPCG assembled symmetric supercapacitor shows ultrahigh energy density of 27.6 Wh kg−1 at a power density of 600 W kg−1. Based on the above advantages, the present work holds a good potential to develop high performance energy storage and conversion devices.

Nicotine contamination in tobacco waste effluent (TWE) from tobacco industry is a serious threat to public health and environment. Microbial degradation is an impending approach to remove nicotine and transform it into some other high value chemicals. Pseudomonas sp. JY-Q exhibits high efficiency of degradation, which can degrade 5 g/L of nicotine within 24 h. In strain JY-Q, we found the co-occurrence of two homologous key enzymes NicA2 and Nox, which catalyze nicotine to N-methylmyosmine, and then to pseudooxylnicotine via simultaneous hydrolysis. In this study, recombinant NicA2 and Nox were expressed in E. coli BL21(DE3) and purified. In vitro, the activity of recombinant NicA2 and Nox was accelerated by adding co-factor NAD+, suggesting that they worked as dehydrogenases. The optimal reaction conditions, substrate affinity, catabolism efficiency, pH-stability and thermal-stability were determined. Nox showed lower efficiency, but at a higher stability level than NicA2. Nox exhibited wider pH range and higher temperature as optimal conditions for the enzymatic reaction. In addition, The Nox showed higher thermo-stability and acid-stability than that of NicA2. The study on enzymatic reaction kinetics showed that Nox had a lower Km and higher substrate affinity than NicA2. These results suggest that Nox plays more significant role than NicA2 in nicotine degradation in TWE, which usually is processed at low pH (4–5) and high temperature (above 40 °C). Genetic engineering is required to enhance the affinity and suitability of NicA2 for an increased additive effect on homologous NicA2 and Nox in strain JY-Q.