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AIM: To investigate the behavioral and psychological disorders and the prevalence of parent ratings of attention deficit hyperactivity disorder (ADHD) symptoms among children with bilateral congenital cataracts (CCs). METHODS: This cross-sectional study investigated children with bilateral CC aged 3-8y (CC group) using Conners' Parent Rating Scale-48 (CPRS-48) from July to December 2016. The abnormal rates of psychological symptoms in CC children and normal vision (NV) children were compared using the Chi-square test. The scores of CC children were compared with those of NV children and the Chinese urban norm using the independent samples t-test and one-sample t-test, respectively. RESULTS: A total of 262 valid questionnaires were collected. The ratio of CC children to NV children was 119:143. The overall rate of psychological symptoms in CC children was 2.28 times higher than that in NV children (46.22% vs 20.28%, Pearson's χ(2)=20.062; P

For low energy consumption and operational stability, multimode equivalent energy consumption, an optimal energy management and control method, is proposed in this paper. This method effectively solves the problem of energy distribution between the primary power—a high-power fuel cell and an auxiliary power—and a supercapacitor, in complex operating conditions. In all four states of the hybrid electric tram, i.e., traction, coasting, braking, and station parking, the optimal energy distribution method, with the highest energy efficiency of the tram, is obtained through the whole system modeling and the equivalent energy consumption calculation. In order to verify the responding speed, this method gets the analytical solution and is tested on the RT-LAB hardware-in-the-loop simulation platform. The results show that compared to the power following method the new method can reduce the overall tram energy consumption by 2.5% in complex operating conditions. What is more, when this method is successfully applied to the world's first commercial fuel cell/supercapacitor LF-LRV hybrid tram, its energy consumption and fuel cell system (FCS) output fluctuation rate are effectively reduced according to the operational data, which indicates a good chance of extending the life of the FCS as well.

This paper first focuses on the study of the relationship between the urban heat island (UHI) and the selected physical variables (percentage of urban surface covers, Normalized Difference Vegetati...

With the fast development of DC Microgrid (MG) technology, its operating economy and reliability are getting more and more concern. The traditional distributed control method is aimed at power balance and system stability, and is difficult to meet the requirement of energy management system for multi-source hybrid DC MG. This paper provides a two-level energy management strategy for PV-fuel cell-battery-based DC MG, which is divided into device control level and system control level. At the device control level, the distributed control methods based on MPPT-droop dual-mode control and droop control are proposed to enhance system reliability; at the system control level, the equivalent consumption minimization strategy (ECMS) is used to distribute system net power between battery pack and fuel cell system. A lab-scale DC microgrid platform is developed to verify the proposed energy management strategy in this paper. Moreover, the analysis and compare of the results show that the proposed two-level energy management strategy can achieve lower equivalent hydrogen consumption than classical PI control and state machine control method.

A novel high-sensitive tilt sensor is proposed and experimentally demonstrated based on the macro-bending loss of single mode fiber (SMF), and its sensitivity can be improved by forming multiple fiber laps. The tilt sensor is formed by an SMF bend into a semicircle with radius small enough to acquire the macro-bending loss, and it is fixed in a vessel with suitable amount of liquid. The surrounding refractive index around the semicircle changes along with the liquid level when the vessel is tilted. According to theoretical derivation, the macro-bending loss is related to the tilted angle, which means the angle can be modulated from the measured macro-bending. The experiment result corresponds to theoretical prediction and shows that the sensor has a high tilted angle sensitivity, which reaches −0.074 dB/degree in the initial scheme and −0.188 dB/degree in two turns situation. The detectable range of the tilted angle is from −90° to 90° in the improved scheme. The temperature influence is also theoretically predicted in this paper.

Optimized robust control for proton exchange membrane (PEM) fuel cell air supply systems is now a hot topic in improving the performance of oxygen excess ratio (OER) and the net power. In this paper, a cascade adaptive sliding mode control method is proposed to regulate oxygen excess ratio (OER) for proton exchange membrane (PEM) fuel cell air supply systems. Based on a simplified sixth-order nonlinear dynamic model, which takes parametric uncertainties, external disturbances and measurement noises into consideration, the nonlinear controller based on cascade adaptive sliding mode (NC-ASM) control is proposed. The method combines the nonlinear terms of super twisting algorithm and two added linear terms, and the modified second order sliding mode (SOSM) algorithm based on an observer is employed to form a cascade structure. Besides, an adaptive law is also utilized to regulate the parameters of the NC-ASM controller online. The performance of the controller is implemented on a real-time emulator. The results show that the proposed strategy performs better than the conventional constant sliding mode (CSM) control and PID method. Though during large range of load current and in the presence of various uncertainties, disturbances and noises, the NC-ASM controller can always converge rapidly, the feasibility and effectiveness are validated.

In order to improve the robustness of the energy management system (EMS) and avoid the influence of demand power on the design of EMS, a coupled power-voltage equilibrium strategy based on droop control (CPVE-DC) is proposed in this paper. Making use of the principal that the DC bus can directly reflect the changes of load power, the proposed strategy couples DC bus voltage with output powers through droop control to achieve self-equilibrium. The proposed EMS is applied into a hybrid tramway model configured with multiple proton exchange membrane fuel cell (PEMFC) systems, batteries and super capacitors (SCs). FC systems and SC systems are responsible for satisfying most of the demand power, therefore the CPVE-DC strategy generates FCs and SCs reference power through power-voltage droop control on the primary control. Then batteries supplement the rest part of load power and generate DC bus voltage reference value of the next sampling time. With the gambling between output power and DC bus voltage, the hybrid system achieves self-equilibrium and steps into steady operation by selecting appropriate droop coefficients. Then the secondary control of the proposed strategy allocates power between every single unit. In addition, a penalty coefficient is introduced to balance SOC of SCs. The proposed strategy is tested under a real drive cycle LF-LRV on RT-LAB platform. The results demonstrate that the proposed strategy can achieve self-equilibrium and is effective to allocate demand power among these power sources，achieve active control for the range of DC bus voltage and SOC consensus of SCs as well. In addition, some faults are simulated to verify the robustness of the proposed strategy and it turns out that the CPVE-DC strategy possesses higher robustness. Finally, the CPVE-DC strategy is compared with equivalent consumption minimization strategy (ECMS) and the results shows that the proposed strategy is able to get higher average efficiency and lower equivalent fuel consumption.

A design of high-temperature superconducting bandpass filter based on split-ring resonator (SRR) structures is presented in this paper. The SRR has been considered as a classical element for metamaterials and exhibits characteristics of subwavelength resonator, hence can aid in the compact design of filters. Filter has been simulated and optimized using Sonnet software. The measured results of the filter have good consistency with the simulated results and show good band pass characteristics. The center frequency of the filter measured at 70 K was 2.515 GHz, the rectangle coefficient was 1.22, and the insertion loss was 0.1 dB at the center frequency.

This paper introduces a state machine control based on the equivalent consumption method for fuel cell/supercapacitor hybrid tramcar is proposed. By the effective combination with a state machine, the coordinate control of multiple power sources enhances the performance of equivalent consumption minimization strategy, increases the fuel cell operating time in a range of high efficiency, and reduces the fluctuation of fuel cell. Moreover, the proposed approach can effectively reduce the hydrogen consumption and keep the system-on-a-chip (SOC) of supercapacitor at a reasonable level. By constructing the RT-LAB semiphysical hardware platform, this method is compared with state machine strategy and equivalent consumption minimization strategy. The hydrogen consumption of the proposed method is reduced by 4.18% compared with the state machine strategy, and reduced by 0.56% compared with the equivalent consumption minimization strategy. Then, the result demonstrates that the proposed method has a better performance. Hence, this new method will have a good application prospect in the high-power hybrid tramway.

The efficiency of a proton exchange membrane fuel cell system (PEMFCS), which includes a PEMFC stack and a dc/dc converter, depends on the applied voltage and there exists an efficiency extreme point (EEP) in PEMFCS. Therefore, the EEP of PEMFCS changes with varying load, because the system parameters are also varying. It makes EEP tracking (EEPT) a challenging assignment. In order to achieve the EEP operation of PEMFCS under varying load conditions without oscillation, this paper proposes a novel EEPT method based on a forgetting factor recursive least square (FFRLS) online identification. The FFRLS algorithm is based on data-driven and uses real-time data of the system to improve the estimation accuracy of PEMFCS parameters under the changing load. On the test bench of PEMFCS-battery system consists of 300-W PEMFCS, lithium-ion battery, PEMFC controller, and DSP controller, a multi-index performance test and comparative analysis were carried out. The results showed that the proposed method is not sensitive to load conditions. The performance of the proposed EEPT method for PEMFCS has been successfully validated. In addition, compared with the “perturb and observe” and “incremental conductance” online tracking algorithms, the proposed online identification method can get more satisfactory results. Such as, reducing the tracking time and hydrogen consumption, making the output power of PEMFCS smoother, which means its operation stress is smaller, and thus, it lasts longer.

AIM: To evaluate the effect of different lens constant optimization methods on the accuracy of intraocular lens (IOL) power calculation formulas for highly myopic eyes. METHODS: This study comprised 108 eyes of 94 consecutive patients with axial length (AL) over 26 mm undergoing phacoemulsification and implantation of a Rayner (Hove, UK) 920H IOL. Formulas were evaluated using the following lens constants: manufacturer's lens constant, User Group for Laser Interference Biometry (ULIB) constant, and optimized constant for long eyes. Results were compared with Barrett Universal II formula, original Wang-Koch AL adjustment method, and modified Wang-Koch AL adjustment method. The outcomes assessed were mean absolute error (MAE) and percentage of eyes with IOL prediction errors within ±0.25, ±0.50, and ±1.0 diopter (D). The nonparametric method, Friedman test, was used to compare MAE performance among constants. RESULTS: Optimized constants could significantly reduce the MAE of SRK/T, Hoffer Q, and Holladay 1 formulas compared with manufacturer's lens constant, whereas the percentage of eyes with IOL prediction errors within ±0.25, ±0.50, and ±1.0 D had no statistically significant differences. Optimized lens constant for long eyes alone showed non-significant refractive advantages over the ULIB constant. Barrett Universal II formula and formulas with AL adjustment showed significantly higher accuracy in highly myopic eyes (P

Corneal neovascularization (CNV) is one of the major causes of severe disorders in ocular surface. Subconjunctival administration provides a localized and effective delivery of anti-angiogenic agents to inhibit neovascularization. In the present study, the ABA triblock copolymer of poly(D,L-lactic-co-glycolic acid)-block-poly(ethylene glycol)-block-poly(D,L-lactic-co-glycolic acid) (PLGA-PEG-PLGA) was used as a sustained drug delivery carrier for metformin (MET) and levofloxacin hydrochloride (LFH). Both drugs and PLGA-PEG-PLGA copolymers could be easily dissolved in water at low or room temperature and the mixed solution could form a drug-loaded thermosensitive hydrogel in terms of body temperature response. The in vitro release investigation displayed a sustained release of MET and LFH from the formulation for one month. The in vivo efficacy of subconjunctival injection of the MET + LFH loaded thermosensitive hydrogel in inhibiting CNV was evaluated on a mouse model of corneal alkali burn. Compared with the single administration of MET or LFH loaded thermosensitive hydrogel, the MET + LFH loaded thermosensitive hydrogel remarkably inhibited the formation of CNV. The sustained release of MET and an antibiotic (LFH) provides synergistic therapeutic outcome. As a result, the co-delivery of MET and LFH using PLGA-PEG-PLGA thermosensitive hydrogel by subconjunctival injection has great potential for ocular anti-angiogenic therapy.

This study aimed to develop a stable and biodegradable tacrolimus loaded nanocarrier that enhanced tacrolimus corneal penetration and delivered in a sustained manner, thus to create a promising treatment to prevent immune rejection after corneal allografts. Spherical tacrolimus loaded methoxy poly (ethylene glycol)-block-poly (D,L)-lactic-co-glycolic acid (mPEG-b-PLGA) micelles with a mean diameter of 81.3 ± 1.3 nm were prepared by the solvent-evaporation-induced self-assembly. The physicochemical properties of tacrolimus loaded mPEG-b-PLGA micelles were evaluated, and the in vitro release behavior, degradation, cytotoxicity and bio-safety were all assessed. The ex vivo permeation of tacrolimus using rabbit corneas was also performed, and the cumulative permeation amount of tacrolimus from mPEG-b-PLGA micelles was significantly higher than 0.05% tacrolimus eye drops (p 0.05). These results indicated that the formulations were feasible for intraocular drug delivery. Compared with 0.05% tacrolimus eye drops, the in vivo immunofluorescence analysis indicated the tacrolimus loaded mPEG-b-PLGA micelles remarkably inhibit the immune rejection after corneal allograft, with the lower expression levels of nuclear factor of activated T cells (NFAT), cluster of differentiation 4 (CD4) and cluster of differentiation 8 (CD8). In conclusion, we provided evidences that tacrolimus loaded mPEG-b-PLGA micelles would be a promising treatment for immune rejection after corneal transplantation.

With the increasing applications of wind energy & power technologies, the stochastic fluctuation and reverse peak load regulation characteristic of wind power brings great challenges to unit commitment of power systems. It is difficult to meet the demand of the peak load regulation with the wind power integration for the existing robust unit commitment models when only considering the cost. In order to solve this problem, an additional objective function of the ability of peak load regulation is constructed for unit commitment solutions. As a result, a novel multi-objective robust unit commitment model considering both the cost and peak load regulation is proposed. Moreover, probabilistic scenario analysis is applied to constraint the model of the fluctuant wind power, and temporal correlation of wind powers is also considered to further improve the economy in the long run. In order to deal with multi-objective problem for the robust optimization solutions, the above-mentioned problem is decomposed into two stages, i.e., a main problem and a subproblem. The main problem is to determine unit commitment and the subproblem is a "min–max optimization" one to obtain the unit outputs. Finally, the simulation analysis based on IEEE118 node system verified the robustness and the validity of the proposed model.

For purpose of solving the data-driven failure diagnosis problems of the proton exchange membrane fuel cell (PEMFC) system, improve the test accuracy and shorten the training time, a novel failure diagnosis method of the PEMFC systems based on data fusion is proposed, which combines extreme learning machine (ELM) and Dempster–Shafer (D-S) evidence theory. The characteristic vector extraction is carried out on the electrical quantities and the nonelectrical quantities of the PEMFC system under four different faults. The kernel ELM algorithm and online sequential ELM algorithm are, respectively, used to establish the failure diagnosis model of the PEMFC system based on electrical quantities and nonelectrical quantities. It is used for preliminary failure diagnosis of a PEMFC system. The diagnosis results of the above-mentioned two strategies are converted into the function values of the basic probability assignment by the squeeze function. The D-S evidence theory algorithm is used to fuse the diagnostic output at the decision level. The classification results of 154 samples of PEMFC system show that the novel model can diagnose four different degrees of high air stoichiometry failures. The average recognition rate is 98.70% and the operation time is only 0.2011 s. At the same time, the comparisons with the back-propagation neural network and one-against-one support vector machine show that the data fusion algorithm can significantly improve the running speed while ensuring the correct recognition rate. It can be used for online failure diagnosis of the PEMFC systems.

The proton exchange membrane fuel cell (PEMFC) stacks are not widely used in the field of transportation industry, due to their limited power. Thus, the PEMFC stacks usually connected in parallel or series to meet the load demand power in high-power applications. The hydrogen consumption of multi-stack fuel cells (MFCs) system is related to the efficiency and output power. In addition, the efficiency of PEMFC depends on the applied voltage and other parameters. Consequently, the hydrogen consumption of system changes with varying load, because the system parameters are also varying. It makes reducing the fuel consumption of system a challenging assignment. In order to achieve the goal of minimizing fuel consumption of parallel-connected PEMFCs system, this paper proposes a novel power distribution strategy based on forgetting factor recursive least square (FFRLS) online identification. The FFRLS algorithm is based on data-driven and uses real-time data of the system to improve the estimation accuracy of PEMFC system parameters. On the test bench of parallel-connected PEMFCs system consists of two 300 W PEMFC stacks, PEMFC stack controller, DC/DC converters, and DSP controller etc., a multi-index performance test and comparative analysis are carried out. The results showed that, the performance of proposed power allocation strategy has been successfully validated. In addition, compared with the power average and daisy chain algorithms, the proposed online identification power distribution method can get more satisfactory results. Such as, reducing the hydrogen consumption and improving efficiency.

In this paper, a hierarchical state machine energy management control method based on minimum cost algorithm is proposed. This method consists two layers, the bottom layer is responsible for the control of each devices while the top layer uses state machine strategy and minimum utilization algorithm to distribute power for each micro sources. Combining the minimum utilization cost theory with the state machine control method, the control system can optimize the utilization cost and energy storage level of the electric-hydrogen hybrid energy storage system under the premise of meeting the requirements of the basic operation of the microgrid. Through the centralized management of the top layer and the control of the bottom layer, the method completes the operation target of the microgrid, thus improving the energy utilization rate and reducing the utilization cost of the system. The real time simulation is carried out through the RT-LAB semi physical system. By a 72 h online operation under actual conditions, the effectiveness of the proposed method is verified, which ensures the low cost and stability of the island DC microgrid with electric-hydrogen hybrid energy system.

This paper investigates the issue of performance optimization for proton exchange membrane fuel cell (PEMFC) system. In PEMFC system, the system efficiency is the key parameters to evaluate the system performance which is sensitive to the air flow rate. Thus, the careful selection of the air flow rate is crucial to ensure efficient, reliable and durable operation of the PEMFC system. In this paper, the dynamic response of the system under variable air flow rate is studied in detail by means of experiments on the built 5 kW PEMFC system with 110 cells and a catalyst active area of 250 cm2. The oxygen excess ratio (OER) is defined to indicate the state of oxygen supply. The experimental results show that the maximum efficiency is existed under certain net current. The OER conditions have the optimal characteristic for system efficiency. Through the optimization of system performance, the system efficiency can be increased by 12.2% on average. At the same time, the system dynamic characteristic under oxygen starvation and oxygen saturation are analyzed in detail based on the experimental data.

Background The ideal surgical timings for cataract extraction (CE) and intraocular lens (IOL) implantation are vital for vision reconstruction in patients with childhood cataract (CC), yet they still remain controversial. We aimed to analyze the real-world practical pattern of surgical timings of CE and IOL implantations among a large number of Chinese CC patients. Materials and methods This cross-sectional, database study included CC inpatients from the *** over a 10-year period (from January 2005 to December 2014). Binary logistic regression and multiple linear regression analyses were performed to identify the factors affecting the timings of CE and IOL implantation. Results In the primary surgical stage, the mean ages of patients performed with CE (n = 839) and CE + IOL implantation (n = 1582) were 9.99 ± 18.21 months (5th-95th percentiles: 2–21) and 82.99 ± 52.99 months (5th-95th percentiles: 24–194), respectively. Surgical age, laterality, and axial length were identified as three factors (area under the curve [AUC]: 0.96, 95% CI: 0.94–0.97; Youden index: 0.86) affecting surgical procedure selection (CE or CE + IOL implantation) in the primary surgical stage. The time intervals between primary CE and secondary IOL implantation in bilateral (n = 311) and unilateral (n = 90) aphakia were 38.25 ± 16.84 months (5th-95th percentiles: 18–72) and 25.87 ± 10.56 months (5th-95th percentiles: 11–48), with significant difference (p Conclusions The timings of CE and IOL implantation mainly varied with the age and laterality. This study may provide data-based clinical experience for ophthalmologists regarding CE and IOL implantation of CC in China and other countries with similar socioeconomic conditions.

The scenario generation method is of great significance to analysis the optimal operation of power system with random variables. However, in case of several wind farms are contained in the power system, it is difficult to precisely generate the scenarios due to the dependence among the wind power output. To solve this problem, a new scenario generation method considering the dependence of multi-wind power output based on the mixture vine copula is proposed in this paper. In this method, the K-means method, C-vine and D-vine copula method are combined to analysis the dependence of the multi-wind power output. Through the proposed method, the precise description of data characteristic of multi-wind power output can be achieved. To verify the accuracy of this method, simulation is conducted by using the measured outputs of three adjacent wind farms. The numerical results show that a better simulation can be obtained by the proposed scenario generation method compared to the existing ways. Further, research on capacity allocation of system with wind/hydrogen production is performed based on the proposed scenario generation method. The result demonstrates the great importance of the proposed scenario generation method to the power system with wind/hydrogen production.

This research presents an optimum design scheme and a hierarchical energy management strategy for an island PV/hydrogen/battery hybrid DC microgrid (MG). In order to efficiently utilize this DC MG, the optimum structure and sizing scheme are designed by HOMER pro (Hybrid Optimization of Multiple Energy Resources) software. The designed structure of hydrogen MG includes a PV generation, a battery as well as a hydrogen subsystem which composes a fuel cell (FC) system, an electrolyzer and hydrogen tank. To improve the robustness and economy of this DC MG, this study schedules a hierarchical energy management method, including the local control layer and the system control layer. In the local control layer, the subsystems in this DC MG are controlled based on their inherent operating characteristics. And the equivalent consumption minimization strategy (ECMS) is applied in the system control layer, the power flow between the battery and FC is allocated to minimum the fuel consumption. An island DC MG hardware-in-loop (HIL) Simulink platform is established by RT-LAB real-time simulator, and the simulation results are presented to validate the proposed energy management strategy.

Background Most previous studies of circulating tumor cells (CTCs) are based on the CellSearch platform, but CellSearch has a number of limitations. This study aimed to use the LiquidBiopsy system and immunofluorescence to test the human epidermal growth factor receptor 2 (HER2) status of CTCs in patients with breast cancer. Materials and Methods The LiquidBiopsy system was used to detect HER2-positive (HER2 + ) cells in whole blood by microfluidic immunomagnetic bead screening and immunofluorescence assay, according to the manufacturer;s instructions. HER2 expression on CTCs was assessed using the Ariol system, calibrated through spiking experiments of 100 cells (BT474, SKBR3, A431, and MDA-MB-231) and 2.5 × 10 7 white blood cells/mL from healthy donors. Seventy-one patients with breast cancer and 107 non-cancer donors consented to provide blood. Results Based on breast cancer cell lines experiments, HER2 + CTCs were defined as CTCs with HER2 immunofluorescence intensity ≥ 3.5 times higher than the CD45 immunofluorescence intensity (100% sensitivity and 99.9% specificity). Among the 71 patients with breast cancer, 31 (43.7%) had HER2 + tumor. Among the HER2 + patients, 41.9% (13/31) were found to be HER2 + based on CTC ≥ 1, and 25.8% (8/31) were positive based on CTC ≥ 3. In HER2-negative patients by pathologic examination, 1 (2.5%) patient was found to have ≥ 3 HER2 + CTCs, whereas 15 (37.5%) patients had ≥ 1 HER2 + CTC. HER2 + CTCs were detected at all stages, even in early breast cancer, but the detection rate was higher in metastatic breast cancer. Conclusion This proof-of-concept study strongly suggests that HER2 + CTCs can be detected using the LiquidBiopsy system.

In order to study the harmonic resonance characteristics of single-stage photovoltaic (PV) grid-connected/hydrogen production multi-inverter system, the modal analysis method was used to systematically analyze and discuss the resonance problem. First, a three-phase single-stage photovoltaic grid-connected/hydrogen production system simulation model was established, and hydrogen production from water electrolysis was used as a local load. Secondly, this paper applied a modal analysis method that could determine the system resonance frequency, resonance center and the participation degree of each component by constructing the multi-inverter system node admittance matrix. Finally, the Thevenin equivalent model of multi-inverter system was established based on the modal analysis method. The influence of the number of inverters on the resonance characteristics of the system was studied. Compared with the frequency response analysis of the transfer function, the simulation results verify the correctness and effectiveness of the modal analysis method.

To solve the prediction problem of proton exchange membrane fuel cell (PEMFC) remaining useful life (RUL), a novel RUL prediction approach of PEMFC based on long short-term memory (LSTM) recurrent neural networks (RNN) has been developed. The method uses regular interval sampling and locally weighted scatterplot smoothing (LOESS) to realize data reconstruction and data smoothing. Not only the primary trend of the original data can be preserved, but noise and spikes can be effectively removed. The LSTM RNN is adopted to estimate the remaining life of test data. 1154-hour experimental aging analysis of PEMFC shows that the prediction accuracy of the novel method is 99.23%, the root mean square error (RMSE) and mean absolute error (MAE) is 0.003 and 0.0026 respectively. The comparison analysis shows that the prediction accuracy of the novel method is 28.46% higher than that of back propagation neural network (BPNN). Root mean square error, relative error (RE) and mean absolute error are all much smaller than that of BPNN. Therefore, the novel method can quickly and accurately forecast the residual service life of the fuel cell.

Based on the theory of time reversal technique and through the use of temporal dispersive delay lines, this paper presents a demonstration of temporal cloaked signal transmission at microwave frequencies. When compared with a conventional signal processing system, the related dispersive delay lines are not required to provide linear group delay response. Thus the proposal simplifies the system structure for temporal cloaking, avoids the drawbacks of easy detection, easy decoding and easy analysed brought by linear modulation system, and then strengthen the safety and reliability in signal transmission. Theoretical analysis and experimental results validate the proposed system. The proposed method and achieved results indicate potential application in secure communications and data multiplexing subject to channel bandwidth requirements.

The energy management strategy is the key to achieve fuel cell hybrid system operation with high-efficiency and low-energy cost. The widely used energy management strategies are established based on the fixed models of power sources energy consumption and efficiency. However, due to the gradual performance degradation of the fuel cell during the service period, some model parameters will change significantly and the fixed models will become increasingly inaccurate over time. Therefore, this paper established time-varying models of power sources energy consumption and efficiency by introducing the fuel cell degradation rate. On this basis, in order to reduce the energy consumption of the system, improve the fuel cell efficiency and relatively maintain the SOC level, a novel dual-mode energy management strategy, DMDEE, for hybrid vehicles was proposed. In order to improve the online operation speed of proposed energy management strategy, the optimal control rules were obtained by offline calculation first. Then through comparison experiments with other two energy management strategies, PMP and PF, it was verified that the proposed strategy can effectively reduce the system energy consumption and improve the efficiency of the fuel cell system, meanwhile could make the SOC regress after its deviating from ideal working area. In addition, the mode switching hysteresis control was also validated. Therefore, the effectiveness and superiority of the proposed energy management strategy in this paper has been verified.

The introduction of hydrogen energy storage system (HESS) as a potential form of energy storage systems (ESSs) has a significant impact on original control and operation. This paper presents a hierarchical self-regulation control method, which can be divided into the supervisory layer and local layer control. The supervisory layer control decides the output power of ESSs, according to the operation cost function so that the system can reach economic optimum during the operation process. The local layer control adopts virtual inertia control with global power support to improve system stability. First, a HESS model composed of an electrolyzer, hydrogen storage tank, and the fuel cell is established. SOCH of hydrogen tank is defined to express produced and consumed hydrogen. Then, aiming at supervisory layer control, operation cost functions of battery energy storage system (BESS) and HESS under different operation modes are built. Virtual inertia of ac ESS and virtual capacitance of dc ESS are introduced for local layer control. Finally, the simulation results based on the RT-LAB platform of both 24-h operation case and step power change case verify the correctness of the proposed method. The comparison with only droop control method shows that the proposed method can achieve the lowest operation cost and improve system inertia.

A capacitor made of high-temperature superconducting (HTS) electrode plates and a dielectric layer, or “HTS capacitor” for short, has the potential advantages of working with other HTS devices at 77 K and producing low conductive loss at high frequency. It may have a specific application to cryogenic systems at high frequency, such as superconducting wireless power transfer (SWPT) systems. Working with HTS resonant coil in an adiabatic container, the HTS capacitor can also reduce the heat leakage of the cooling system. Considering a lack of relevant experimental study at present, an HTS capacitor composed of YBCO (YBa2Cu3O7- $_x$ ) tapes and a polyimide layer is proposed in this paper and tested in an SWPT system. Its characteristics and influences on the SWPT system are presented in detail by theoretic analysis and experimental investigation. A comparative experiment is carried out between the fabricated HTS capacitor and other capacitors made from normal materials. Finally, it is confirmed experimentally that the HTS capacitor can have a high-quality factor, work with the HTS resonant coil normally at 77 K, and provide the SWPT system with a performance enhancement.

For solving the problem of sequence failure diagnosis of proton exchange membrane fuel cell (PEMFC) water management subsystem, this paper proposes a PEMFC failure diagnosis method of time series based on the bidirectional long short-term memory (BiLSTM) network and t-distributed stochastic neighbor embedding (t-SNE). This approach adopts the normalization strategy to eliminate the influence caused by dimensional differences of different parameters. The t-SNE is presented to decrease the dimensionality of normalized data to the estimate of intrinsic dimensionality to extract key characteristic variables. The width of the diagnostic window is set to transform the original single moment diagnosis problem into the fault diagnosis problem of multi-variable time series, which is more consistent with the time scale and physical evolution law of the PEMFC water management fault generation. The 672 sets of training sets and 448 sets of test sets are learned and tested by the BiLSTM. The experimental results show that the BiLSTM-tSNE method can realize the sequence fault diagnosis of the PEMFC water management subsystem with 96.88% diagnostic accuracy and 24 s of operation time. Compared with the conventional approach of multi-class support vector machine algorithm, the training accuracy and the testing accuracy of the proposed method are improved by 15% and 16.88%, respectively. The operation time of the presented approach is only about 1/28 of the multi-class support vector machine algorithm.

The aging trajectory prognosis is an effective tool to prolong the lifespan and lower the cost of proton exchange membrane fuel cell (PEMFC) systems. In this paper, Gaussian process regression modeling frameworks based on sparse pseudo-input Gaussian process (SPGP) and variational auto-encoded deep Gaussian process (VAE-DGP) are proposed to predict the degradation trend and cope with model uncertainty for PEMFCs. The optimal hyper parameters and pseudo-input locations are obtained with conjugate gradient by maximizing the marginal likelihood. Besides, the variational parameters and closed-form variational lower bound are optimized through variable inference, radial basis function (RBF) kernel is utilized to determine the priori distribution of Gaussian process. Then stack voltage and output power are extracted as health indicators (HIs). To fully demonstrate the prediction performance, long-term experimental validation with static and dynamic aging tests are performed, single-input and multi-input structures are respectively constructed in SPGP and VAE-DGP for comparison with the existing models. The results show that the proposed methods outperform other data-driven methods, moreover, SPGP is more suitable for large data regime and VAE-DGP operates better with small data regime. Finally, the performance evolution is presented with 95% confidence interval to validate the mapping accuracy and reliability further.

The intermittent and irregular characteristics of the renewable power generation bring about tremendous technical challenges for large-scale deployment and efficient management. Aiming at this problem an islanded microgrid system with an electric-hydrogen hybrid energy storage system is established. In the islanded microgrid system, the hydrogen storage device mainly includes the electrolytic cell, the fuel cell, and the hydrogen storage tank. The energy storage system is clean and pollution free, which can improve the utilization rate of renewable power generation and stabilize the DC bus voltage fluctuation. Each unit collects and distributes energy to the DC bus through a DC/DC converter and energy management strategy. To provide a reasonable planning of the islanded microgrid with an electric-hydrogen hybrid energy storage system, a planning optimization method considering unit cost, load loss rate, and excess energy rate is established, and the particle swarm optimization algorithm is used to solve the problem. Under the premise of satisfying the constraints of each component, the capacity allocation scheme under the optimal conditions of a comprehensive economy and power supply reliability index is obtained, and the effectiveness of the proposed method is verified.

Retinal pigment epithelium (RPE), a postmitotic monolayer located between the neuroretina and choroid, supports the retina and is closely associated with vision loss diseases such as age-related macular degeneration (AMD) upon dysfunction. Although environmental stresses are known to play critical roles in AMD pathogenesis and the roles of other stresses have been well investigated, glucose deprivation, which can arise from choriocapillary flow voids, has yet to be fully explored. In this study, we examined the involvement of VEGFR2 in glucose deprivation-mediated cell death and the underlying mechanisms. We found that VEGFR2 levels are a determinant for RPE cell death, a critical factor for dry AMD, under glucose deprivation. RNA sequencing analysis showed that upon VEGFR2 knockdown under glucose starvation, endoplasmic reticulum (ER) stress and unfolded protein response (UPR) are reduced. Consistently, VEGFR2 overexpression increased ER stress under the same condition. Although VEGFR2 was less expressed compared to EGFR1 and c-Met in RPE cells, it could elicit a higher level of ER stress induced by glucose starvation. Finally, downregulated VEGFR2 attenuated the oxidative stress and inflammatory factor expression, two downstream targets of ER stress. Our study, for the first time, has demonstrated a novel role of VEGFR2 in RPE cells under glucose deprivation, thus providing valuable insights into the mechanisms of AMD pathogenesis and suggesting that VEGFR2 might be a potential therapeutic target for AMD prevention, which may impede its progression. Funding Agencies|State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University in Guangzhou; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [81470644]; Key Program of the National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [81330021]; NSFC-VR Collaboration Program of the National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [81611130082]

Purpose. To introduce an effective method for separating extensive posterior synechiae and those located under or adjacent to surgical incisions. Methods. Pediatric patients who had been subjected to cataract surgery and developed troublesome posterior synechiae requiring secondary intraocular lens (IOL) implantation were recruited. All patients underwent microperipheral iridectomy at the 12 o’clock position. Then, an ophthalmic viscosurgical device was injected into the posterior chamber through the iris fistula to mechanically separate the posterior synechiae, using scissors to cut robust posterior synechiae if necessary. The results of posterior synechiolysis and the position of the implanted IOL were analyzed. Results. Sixteen patients (median age, 51.56 months; range, 28–80 months) were included. The scope of posterior synechia in clock was 4.42 (range, 1–10). All troublesome posterior synechiae were successfully separated using the microperipheral iridectomy method, and all patients underwent IOL implantation in the ciliary sulcus. There was one case of peripheral iridectomy-related early intraoperative bleeding; no bleeding was observed at the end of surgery. Conclusions. Microperipheral iridectomy is a useful method for the management of troublesome posterior synechiae during secondary IOL implantation in pediatric patients, which makes secondary IOL implantation an easier and safer method in some challenging cases.

In this chapter the AC microgrid based on virtual synchronous generator (VSG) control is introduced. Firstly the control technology is introduced briefly. Then the feedback quantity of the inner loop in the droop control system is designed by using the transfer function and frequency domain diagram. Secondly the second-order transient mathematical model is selected to design the power frequency controller and excitation regulator of VSG. Considering that the traditional droop control only satisfies the primary frequency regulation, this chapter introduces the method of realizing the frequency tracking without difference by forming the secondary frequency modulation through the integrator to improve the power sharing accuracy and the power frequency characteristics of the AC microgrid. Finally, by establishing the model of AC microgrid based on VSG, the control system designed in this chapter is verified. The simulation results show that the control system of the microgrid has good active and reactive power sharing performance and provides inertia and damping for the system, which improves the power supply quality and stability of the microgrid.

To investigate the demographics and distribution of corneal astigmatism before cataract surgery in patients from western China and to compare and analyze these findings with those of patients in southern China.Clinical-based cross-sectional study.Patients undergoing cataract surgery in the People's Hospital of Xinjiang Uygur Autonomous Region from February 2012 to August 2019 were recruited. Preoperative keratometric data measured by performing preoperative bilateral partial coherence interferometry (IOLMaster), and patient demographics were recorded and analyzed.This study comprised 12,236 eyes of 7065 patients with a mean age of 64.75 ± 9.66 years, and 52.77% of the patients were female. The mean axial length was 23.14 ± 0.96 mm. Astigmatism ranged from 0 diopters (D) to 6.94 D, with a mean of 1.28 D. Corneal astigmatism was between 0.25 D and 1.25 D in 53.71% of eyes, 1.25 D or higher in 39.06% eyes, and less than 0.25 D in 7.23% of eyes. Astigmatism was with the rule (WTR) in 41.94% of the patients and against the rule (ATR) in 38.80% of patients. The mean flat and steep keratometry measurement was 43.19 ± 1.50 D and 44.24 ± 1.62 D, respectively. After matching, corneal astigmatism in western China was 1.30 ± 1.03 D, and it was significantly higher than that in southern China (0.98 ± 0.67 D,Corneal astigmatism in patients before cataract surgery in western China was mainly between 0.25 D and 1.25 D. Compared with patients in southern China, patients in western China are younger, have a much higher degree of astigmatism, and have a higher proportion of WTR astigmatism.

To settle the failure detection conundrum of the PEMFC power generation system, a failure detection approach of the PEMFC power generation system ground on local reservation projection (LLP) and learning vector quantization neural network (LVQNN) is devised. In this method, normalized preprocessing and LLP algorithms are used to shorten the dimensionality of the primary data, and the LVQNN is used to identify the pre-processed data. The results of 600 groups of fault data of the PEMFC water management subsystem reveal that the proposed approach can diagnose the faults of the PEMFC power generation system with 98.33% accuracy and can apply to the failure detection field of PEMFC power generation system.

Summary Background Medical artificial intelligence (AI) has entered the clinical implementation phase, although real-world performance of deep-learning systems (DLSs) for screening fundus disease remains unsatisfactory. Our study aimed to train a clinically applicable DLS for fundus diseases using data derived from the real world, and externally test the model using fundus photographs collected prospectively from the settings in which the model would most likely be adopted. Methods In this national real-world evidence study, we trained a DLS, the Comprehensive AI Retinal Expert (CARE) system, to identify the 14 most common retinal abnormalities using 207 228 colour fundus photographs derived from 16 clinical settings with different disease distributions. CARE was internally validated using 21 867 photographs and externally tested using 18 136 photographs prospectively collected from 35 real-world settings across China where CARE might be adopted, including eight tertiary hospitals, six community hospitals, and 21 physical examination centres. The performance of CARE was further compared with that of 16 ophthalmologists and tested using datasets with non-Chinese ethnicities and previously unused camera types. This study was registered with ClinicalTrials.gov , NCT04213430 , and is currently closed. Findings The area under the receiver operating characteristic curve (AUC) in the internal validation set was 0·955 (SD 0·046). AUC values in the external test set were 0·965 (0·035) in tertiary hospitals, 0·983 (0·031) in community hospitals, and 0·953 (0·042) in physical examination centres. The performance of CARE was similar to that of ophthalmologists. Large variations in sensitivity were observed among the ophthalmologists in different regions and with varying experience. The system retained strong identification performance when tested using the non-Chinese dataset (AUC 0·960, 95% CI 0·957–0·964 in referable diabetic retinopathy). Interpretation Our DLS (CARE) showed satisfactory performance for screening multiple retinal abnormalities in real-world settings using prospectively collected fundus photographs, and so could allow the system to be implemented and adopted for clinical care. Funding This study was funded by the National Key R&D Programme of China, the Science and Technology Planning Projects of Guangdong Province, the National Natural Science Foundation of China, the Natural Science Foundation of Guangdong Province, and the Fundamental Research Funds for the Central Universities. Translation For the Chinese translation of the abstract see Supplementary Materials section.

BACKGROUND: Although influencing the severity of postoperative intraocular inflammation of congenital cataract, the developmental characteristics of cytokine profile in the aqueous humor during childhood had not been described. And its relationship with the inflammatory response after intraocular surgery remained unsolved. METHODS: Preoperative aqueous humor samples were collected from 65 eyes of congenital cataract patients (CC group) and 13 eyes of age-related cataract patients (ARC group) from January 2015 to May 2017. The concentrations of 22 cytokines were measured. Differences in concentrations between the CC and ARC groups were described. Correlation analysis, least absolute shrinkage and selection operator (LASSO) and multivariate linear regression were then used to investigate the dynamic changes in the cytokine profile with age and their relationships with the postoperative inflammatory response. RESULTS: The concentrations of granulocyte colony stimulating factor (G-CSF), interferon (IFN)-α2, interleukin (IL)-1α and IL-7 were higher in the CC group than in the ARC group, while the concentrations of epidermal growth factor (EGF), granulocyte-macrophage colony stimulating factor (GM-CSF), IL-10, IL-12p70, IL-2, IL-3, IL-4, IL-5, IL-6, IL-8, and tumor necrosis factor (TNF)-α were more abundant in the ARC group (P

A four-channel serpentine flow-field proton exchange membrane fuel cell model is built based on the conservation equations and reaction mechanisms using COMSOL Multiphysics. This paper analysis the impacts of the mass transport on the fault state. The cathode pressure-drop increases exponentially in the concentration polarization region, demonstrating its sensitivity under PEMFC fault state. When the voltage drops from open circuit voltage to 0. 3V, the average molar concentration increases from 0.97789 mol $/m^{3}$ to 8.3663 mol $/m^{3}$ of water, reduces from 5.4324 mol $/m^{3}$ to 0.8979 mol $/m^{3}$ of oxygen, and decreases from25.815 mol $/m^{3}$ to 18.951mol/m3 of hydrogen. The results indicates that water flooding and oxygen starvation are the primary causes of performance degradation and pressure-drop rises.

Webly supervised learning becomes attractive recently for its efficiency in data expansion without expensive human labeling. However, adopting search queries or hashtags as web labels of images for training brings massive noise that degrades the performance of DNNs. Especially, due to the semantic confusion of query words, the images retrieved by one query may contain tremendous images belonging to other concepts. For example, searching `tiger cat' on Flickr will return a dominating number of tiger images rather than the cat images. These realistic noisy samples usually have clear visual semantic clusters in the visual space that mislead DNNs from learning accurate semantic labels. To correct real-world noisy labels, expensive human annotations seem indispensable. Fortunately, we find that metadata can provide extra knowledge to discover clean web labels in a labor-free fashion, making it feasible to automatically provide correct semantic guidance among the massive label-noisy web data. In this paper, we propose an automatic label corrector VSGraph-LC based on the visual-semantic graph. VSGraph-LC starts from anchor selection referring to the semantic similarity between metadata and correct label concepts, and then propagates correct labels from anchors on a visual graph using graph neural network (GNN). Experiments on realistic webly supervised learning datasets Webvision-1000 and NUS-81-Web show the effectiveness and robustness of VSGraph-LC. Moreover, VSGraph-LC reveals its advantage on the open-set validation set., Accepted to ACM Multimedia 2020 (Oral)

Background Liquid-phase concentrated growth factor (LPCGF), a new-generation platelet concentrate, may potently stimulate human periodontal ligament (PDL) cells. This study assessed the effectiveness of ethylenediaminetetraacetic acid (EDTA) and/or LPCGF on periodontally diseased root surfaces through their effects on PDL cells. Methods Dentin blocks prepared from periodontal teeth were divided into four groups and treated as follows: group I, scaling and root planning (SRP); group II, SRP + EDTA; group III, SRP + LPCGF; and group IV, SRP+EDTA + LPCGF. PDL cells were cultured on dentin blocks, and LPCGF-induced biological effects were evaluated by migration and cell adhesion/proliferation assays. Furthermore, PDL cell differentiation was assessed by real-time polymerase chain reaction (PCR). Results Significantly more adherent cells were observed in the EDTA, LPCGF and combination treatment groups than in the control group. Root conditioning with EDTA and/or LPCGF enhanced cell proliferation and migration more than SRP did. Compared with the control group, the combined treatment group exhibited significant upregulation of cell differentiation-related genes. Electron microscopy of the tooth surface revealed removal of the smear layer and exposed dentin holes in the EDTA-treated group but not in the control group. Conclusion EDTA and LPCGF application to periodontitis-affected root surfaces forms a surface suitable for cell attachment, growth, migration and differentiation. Thus, LPCGF is promising in clinical periodontics applications. Further studies to support these results are necessary.

Wide heterogeneity of disease course ranging from asymptomatic spread to respiratory failure and death has become a hallmark of the SARS-CoV-2 pandemic. While this clinical spectrum is well documented, its immunologic underpinnings are less clear. We have therefore, initiated studies of the B cell responses as they would participate in both early effector responses and in the initiation of memory formation. In terms of effector responses, we were particularly interested in the engagement and clinical correlates of the extra-follicular pathway (EF), we recently described in flaring SLE. In this systemic autoimmune disease, the EF pathway is initiated by newly activated naive B cell (aN) leading to large expansion of autoantibody-producing antibody-secreting cells through the generation of an epigenetically primed B cell precursor which are double negative (DN) for naive (IgD) and memory markers (CD27) and lacking expression of CXCR5 and CD21 (DN2). These highly activated D2 cells are also distinguished by high expression of CD11c and T-bet and are TLR7-driven. Both, TLR7-stimulation which is triggered by ssRNA and the central role played by their murine counterparts (typically characterized as Age-Associated B cells), in viral clearance, strongly supported the hypothesis that DN2 cells and the global EF pathway could be prominently engaged in COVID-19 patients. Also of note, EF B cell activation is particularly prominent in SLE patients of African-American ancestry, a population disproportionately represented in severe COVID-19. In this study we find that critically-ill patients with COVID-19 robustly upregulate constituents of the extrafollicular pathway, produce enormous numbers of antibody secreting cells, and lose unique transitional B cell populations that correlate with positive prognosis. This patient cluster associates tightly with biomarkers of poor outcomes and exhibits high rates of mortality. Thus, this B cell phenotype might serve as an immunological marker of severe COVID infection at early stages and could therefore identify a patient subset likely to benefit from targeted immunomodulatory therapy aimed at alleviating disease burden.

During the fuel cell vehicles operation, traditional optimization-based power distribution strategy mostly regards PEMFC as a characteristic-fixed DC power supply, which ignoring the problem that the characteristics of PEMFC will significantly change. And in traditional equivalent hydrogen consumption calculation of energy storage system, it ignores the PEMFC consumption nonlinear characteristics and the brake energy used to charge the energy storage system, resulting the calculation inaccuracy. In order to solve the problem above and optimize the overall energy consumption, this paper proposes an equivalent hydrogen consumption calculation method based on energy storage system historical operation data firstly, then proposes an adaptive power distribution strategy based on the PEMFC parameters online identification. Through the experiments, the effectiveness of the adaptive power distribution strategy is verified.

Wide heterogeneity of disease course ranging from asymptomatic spread to respiratory failure and death has become a hallmark of the SARS-CoV-2 pandemic. While this clinical spectrum is well documented, its immunologic underpinnings are less clear. We have therefore, initiated studies of the B cell responses as they would participate in both early effector responses and in the initiation of memory formation. In terms of effector responses, we were particularly interested in the engagement and clinical correlates of the extra-follicular pathway (EF), we recently described in flaring SLE. In this systemic autoimmune disease, the EF pathway is initiated by newly activated naive B cell (aN) leading to large expansion of autoantibody-producing antibody-secreting cells through the generation of an epigenetically primed B cell precursor which are double negative (DN) for naive (IgD) and memory markers (CD27) and lacking expression of CXCR5 and CD21 (DN2). These highly activated D2 cells are also distinguished by high expression of CD11c and T-bet and are TLR7-driven. Both, TLR7-stimulation which is triggered by ssRNA and the central role played by their murine counterparts (typically characterized as Age-Associated B cells), in viral clearance, strongly supported the hypothesis that DN2 cells and the global EF pathway could be prominently engaged in COVID-19 patients. Also of note, EF B cell activation is particularly prominent in SLE patients of African-American ancestry, a population disproportionately represented in severe COVID-19. In this study we find that critically-ill patients with COVID-19 robustly upregulate constituents of the extrafollicular pathway, produce enormous numbers of antibody secreting cells, and lose unique transitional B cell populations that correlate with positive prognosis. This patient cluster associates tightly with biomarkers of poor outcomes and exhibits high rates of mortality. Thus, this B cell phenotype might serve as an immunological marker of severe COVID infection at early stages and could therefore identify a patient subset likely to benefit from targeted immunomodulatory therapy aimed at alleviating disease burden.

In a hydrogen-based DC microgrid (MG), the integration of hydrogen subsystem increases the system complexity and flexibility. Effective power split, bus voltage stability and reliable operation become significant control issues of hydrogen-based DC MG. This paper proposes a simple and effective decentralized energy management strategy based on a mode-triggered droop scheme for an islanded PV/hydrogen/battery DC MG. In a decentralized manner, the proposed decentralized energy management strategy is implemented through two control steps: mode divisions and droop control. For practical implementation purposes of the proposed energy management strategy, the mode divisions scheme autonomously divides this DC MG into eight operating modes based on the system local information; the adaptive droop control method controls the distributed generation units based on their droop relationships under different operating modes. In addition, an islanded DC MG hardware-in-the-loop (HIL) RT-LAB simulation platform and a lab-scaled experimental platform are built to validate the effectiveness of the proposed decentralized strategy. The simulation and experiment results show that the proposed energy management strategy has an efficient power distribution ability without communication link under various operating modes.