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The estimated field current (EFC) of the main generator (MG) contains information related to the rotor position of the main exciter (ME). Besides, MG and ME are mounted on the same shaft of brushless synchronous starter/generator (BSSG). The electrical and structural features indicate that the sensorless control of MG can be conducted with EFC. Since EFCs are nonlinear and have abundant harmonics, their dynamic features are complex and lack research. Therefore, most of the existing rotor position estimation methods are only based on the steady-state characteristics of EFC, and the rotor position information of EFC is not fully exploited. To improve the dynamic performance, a novel sensorless starting control method of BSSG is proposed. First, the quantitative relationship between EFC and ME rotor position is revealed. According to this relationship, a dedicated demodulation method is designed to obtain the rotating angle of ME. Meanwhile, a novel fast initial rotor position detection method is proposed for MG. Finally, combining the rotating angle of ME and the initial rotor position of MG, a continuous rotor position of BSSG can be obtained. The effectiveness of the proposed method is verified by experiment.

Energy storage systems (ESS) are pivotal component in the energy market, serving as both energy suppliers and consumers. ESS operators can reap benefits from energy arbitrage by optimizing operations of storage equipment. To further enhance ESS flexibility within the energy market and improve renewable energy utilization, a heterogeneous photovoltaic-ESS (PV-ESS) is proposed, which leverages the unique characteristics of battery energy storage (BES) and hydrogen energy storage (HES). For scheduling tasks of the heterogeneous PV-ESS, a practical cost function plays a crucial role in guiding operator’s strategies to maximize benefits. We develop a comprehensive cost function that takes into account degradation, capital, and operation/maintenance costs to reflect real-world scenarios. Moreover, while numerous methods excel in optimizing ESS energy arbitrage, they often rely on black-box models with opaque decision-making processes, limiting practical applicability. To overcome this limitation and enable explainable scheduling strategies, a prototype-based policy network with inherent interpretability is introduced. This network employs human-designed prototypes to guide decision-making by comparing similarities between prototypical situations and encountered situations, which allows for naturally explained scheduling strategies. Comparative results across four distinct cases demonstrate the effectiveness and practicality of our proposed pre-hoc interpretable optimization method when contrasted with black-box models.

In order to support the transmission of orbital angular momentum (OAM) modes effectively, the ring-core fiber has received a lot of attention due to the similar structure of the electric field distribution with the intensity profile of OAM mode. Both photonic crystal fibers and other micro-structured fibers almost contain a ring-core structure to support the transmission of more OAM modes. However, the middle of the ring-core fiber is usually a large air hole, and such a structure makes it difficult to manufacture the ring-core perfectly. Concave damage may occur in the ring-core. The effects of concave damage on the transmission of OAM modes are analyzed. The concave damage leads to a large effective refractive index difference between the odd and even modes of vector mode, and a method for proper compensation is proposed. The lining is added to the inner side of the ring-core, which is made of the same material as the cladding, and slightly increasing the refractive index of the lining material promotes the performance of the compensation. After numerical simulation, the walk-off distance can be increased by a factor of 2–20 after compensation.

Competition and cooperation among agents in multiagent systems can be effectively modeled as differential games. One of the typical tasks is capturing the flag, in which the agents can be divided into attackers’ alliance and defenders’ alliance with two-phase competitive behaviors. The attackers’ alliance aims to capture flags in the first phase and then return to the safe region in the second phase, while the defenders’ alliance aims to protect the flags and apprehend as many attackers as possible. Throughout the interaction, agents are actively involved in perception, cognitive learning, and the formulation of optimal decisions rooted in their acquired knowledge. Consequently, this article delves into the central challenges posed by capture-the-flag differential games, particularly in terms of task allocation and coordinated apprehension strategies among defenders. First, we use the Apollonius circle to transform the multiplayer capture-the-flag problems into one-defense-one or two-defense-one scenarios. By analyzing the advantages of cooperation between defenders, a two-stage joint optimal strategy is obtained. Moreover, we propose an approximation algorithm that achieves optimal task assignment, significantly reducing computational complexity. The performance and effectiveness of the proposed algorithm are demonstrated through numerical simulations.

The wound-rotor synchronous machine has become a competitive candidate for the integrated starter–generator of more electric aircraft. Due to the large inertia of aircraft engine, the armature currents of the main machine (MM) are large and the windings heat up severely. In order to reduce the heat generation during the starting process, it is necessary to research a loss minimization control method of the wound-rotor synchronous machine in the starting mode. Based on the equivalent circuits considering the equivalent iron loss resistance, this article derives the controllable electrical loss function of the MM. Since its field current changes with speed, the derivative term of the field current with respect to time is considered. By solving for the extremum, the reference value for the d-axis current of the minimum loss point is derived and a loss minimization control method for the MM in the starting mode is proposed. Besides, based on the model reference adaptive system, an adaptive law is designed to identify the stator resistance, thereby improving the accuracy of the loss minimization control method. Experiment results show that the proposed method can effectively reduce the controllable electric loss and thus suppress the heat generation during the starting process.

Using the main exciter (ME) as the quasi-resolver is an emerging advanced sensorless control technology. Since the ME becomes a dual-use machine, the structure of a brushless synchronous starter/generator (BSSG) is simplified and more compact. However, the existing rotor position estimation methods in this path are limited to the low-speed range. What is more, the acquisition of the stator parameters of ME is still tedious due to the special structure of BSSG. In this article, a sensorless starting control method of BSSG based on flux and parameter estimation of ME is proposed. First, the relationship between the rotor position and flux is strictly derived, and the low-speed limitation has been removed theoretically. According to this relationship, the rotor position estimation methods of ME and the main generator are then proposed. Besides, taking advantage of the nonlinear operating characteristics of the rotating rectifier, a simple parameter estimation method of ME is proposed. With this method, the stator parameters of ME are estimated with only stator voltages and currents by the recursive least squares algorithm, and rotation is not needed. Finally, the effectiveness of both the sensorless starting control method and the parameter estimation method is verified by experiments.

For an aviation brushless synchronous starter/ generator system, rotors of the main exciter (ME) and main machine (MM) rotate synchronously. Meanwhile, abundant current harmonic in ME's rotor, which is caused by a rotating rectifier, contains rotor position information. Then, the rotor position of MM can be obtained indirectly by signals of ME. In this article, based on rotor current characteristics of the excitation system, the estimated rotor current of ME and MM is employed innovatively for rotor position estimation at low speed. First, the harmonic current characteristics in ME's rotor winding are analyzed, and the low-order harmonic can be used for rotor position increment estimation. However, the rotor current of ME cannot be measured directly. Fortunately, in dq coordinate, it can be estimated by the measurable signal in stator winding. Furthermore, by operations of rotation transformation and low-pass filtering, rotor position increment can be obtained. Meanwhile, by injecting low-frequency rotating signals into MM's stator, the initial rotor position of MM can be obtained by sampling the estimated main field current at a fixed point. Finally, by combining rotor position increment and initial rotor position, sensorless starting control can be realized. The proposed method can avoid the influence of MM's operating state and experiments verify the effectiveness.

Accurate and timely fault diagnosis of the rotating rectifier in aircraft wound-rotor synchronous starter/generator (WRSSG) is very important for improving system reliability. Through the analysis of the stator excitation current of the main exciter (ME) with the rotating rectifier under various working conditions (healthy, open-circuit fault, and short-circuit fault), a novel fault diagnosis method of the rotating rectifier based on ME excitation current amplitude is proposed in this article. In this method, the sum of squared stator currents of the ME is calculated and the position corresponding to the maximum current is obtained, and they are used to calculate the ratio for fault detection. The proposed fault diagnosis method is the first rotating rectifier diode fault diagnosis method that can be applied in the stationary, startup, and generation processes of the system. The experiment results verified the feasibility and effectiveness of the proposed method.

We study the joint battery charging and replenishment scheduling of a battery swapping charging system (BSCS) considering random electric vehicle (EV) arrivals, renewable generation, and electricity prices. We formulate the problem as a Markov decision process with an objective to minimize the expected sum of the operation cost (battery charging and replenishment cost) and the waiting cost of EV customers. The joint scheduling problem is challenging due to the stochasticity in EV arrivals, renewable generation, and electricity prices, as well as the curse of dimensionality in the system state and action spaces. To reduce the dimension of the action space, we propose to integrate structural properties into BSCS operation, i.e., the threshold-charging (TC) and least demand first (LDF) structures into the charging policy, and the $(s, S)$ structure into the replenishment policy (when the number of fully-charged batteries at a battery swapping station is below $s$ , the inventory is replenished to a higher threshold $S$ ). Numerical experiments on real-world data show that the proposed SAC+TC+ $(s, S)$ approach saves 7.16%-78.61% and 6.53%-93.73% of total average cost resulting from various structural charging and replenishment policies and the vanilla soft actor-critic (SAC) algorithm under different settings.

For a battery swapping station (BSS) with solar generation, $N$ charging bays, and an inventory of $M$ batteries, we study the charging scheduling problem under random EV arrivals, renewable generation, and electricity prices. To minimize the expected weighted sum of charging cost (sum of electricity and battery degradation costs) and EV owners’ waiting cost, we formulate the problem as a Markov decision process with unknown state transition probability. Under a mild heavy-traffic assumption, we rigorously establish the optimality of the Less Demand First (LDF) priority rule under arbitrary system dynamics: batteries with less demand shall be charged first. The optimality result enables us to integrate the LDF rule into a state-of-the-art deep reinforcement learning (DRL) method, proximal policy optimization (PPO), reducing the dimensionality of its output from $O(M+N)$ to $O(1)$ , without loss of optimality in the heavy-traffic scenario. Numerical results (on real-world data) demonstrate that the proposed LDF enhanced PPO approach significantly outperforms classical DRL methods and FCFS (first come, first served) priority rule based DRL counterparts.

Ghost imaging (GI) has recently emerged as a promising new imaging technology, generating considerable interest in the field. Using appropriate speckles in GI can result in higher-quality reconstructed target images. The conventional method of projecting random speckles to illuminate unknown targets often results in low efficiency and poor image reconstruction quality. Recently, we find that speckles in GI act similarly to fully-connected layers in neural networks, in terms of information processing and transmission. Therefore, we propose an improved projection method for speckles, called AGOS, which is based on adaptive gradient optimization employing a fully-connected layer. Demonstrations based on simulations and experiments show that the proposed method in this letter can achieve better results than random speckles under the same conditions.

In the flexible hoisting system, past research focused on the physical modeling without considering complex external environmental variables such as guided rails excitation and shaft effect, leading to a significant deviation between the physical model and the actual model. However, the physical modeling is difficult to model the actual dynamics of the rope strictly under the actual working conditions. This paper takes a high-speed elevator hoisting system as an example. A modified model combining the physical model and the data-driven model is proposed to mitigate the deviation between the physical model and the actual model. In the experiments, the vibration signals of the rope were extracted from images collected by a camera. A beat-like phenomenon of the vibration signals is discovered in the vibration signals of the rope during the acceleration stage. The experiment results demonstrate that the modified model can more accurately model the dynamics of the rope under the actual working conditions and reduce the absolute error of 75.9% compared with the physical model. The proposed model also provides a reference for the modification of the complex dynamic models.

Due to the reliability problems of mechanical position sensors, rotor position estimation technology is an alternative for the starting control of aircraft wound-field synchronous starters/generators. Reversible saliency and high-frequency attenuation characteristics of the main machine (MM) may lead to the failure of existing high-frequency signal-based estimation methods. In this article, low-frequency signal (LFS) injection and a novel signal extraction method are combined to estimate rotor position. First, LFS is injected into MM's stator winding, and a response signal containing rotor position information is induced in its rotor field winding. Then, the response signal can be extracted from the estimated main field current (EMFC) by a bandpass filter. Furthermore, the phase of the extracted signal and the injected LFS are obtained by two single-phase phase-locked loops (PLLs), respectively. Then, the increment in the rotor position can be obtained by the two PLLs. Meanwhile, by injecting a specific low-frequency square wave, the initial rotor position can also be extracted from EMFC, requiring no extra pole identification and phase compensation. Finally, by combining the initial rotor position and position increment, a continuous rotor position of MM can be obtained. The effectiveness of the proposed method is verified by experiments.

Owing to the mutual orthogonality among different orbital angular momentums (OAM), OAM mode has been considered as a promising candidate for improving channel capacity and spectrum efficiency. However, the spiral phase-front of OAM mode is susceptible to atmosphere turbulence (AT) in free pace. The distorted spiral phase induces random noise and signal shake (fluctuation) among symbols and then degrades system performance. In order to overcome the issues, an equalization method in frequency-domain is proposed for mitigating the signal shake induced by the AT. For verifying the feasibility and validity of the proposed concept, the corresponding theoretical analysis and experiments are derived and implanted, respectively. The calculated results demonstrate that the signal shake induced by AT can be effectively mitigated when an optimized estimation response matrix is achieved by using a least squares (LS) algorithm. The bit error rate (BER) and constellation plot (CP) of quadrature amplitude modulation (QAM) signal are also investigated to evaluate the system performance, which demonstrate that the proposed concept can effectively resist the AT in an OAM-based free space optical communication system.

It is difficult to implement modeling for overall construction due to the complex structure and distinct environmental influences for the high-speed elevator so researchers rarely achieve end-to-end control for vibration suppression. Meanwhile, the dynamic parameters of the hoist component (the hoist rope) contain more environmental disturbance characteristics than the traction machine. In this paper, a sensitivity analysis of data channels of hoist rope that can help to clarify the effective control loop based on experimental results is implemented. The authors combined a neural network-based (NN-based) regression model and attention module for predicting hoisting rope vibration to achieve over 95% accuracy, and determine the channel data that contributes most to vibration prediction.

This study concentrates on the differential private distributed optimization problem with an event-triggered mechanism, whose goals include preserving the privacy of agents’ initial states and local cost functions and improving communication efficiency. A distributed event-triggered mechanism is integrated into the differentially private subgradient-push distributed optimization algorithm and then a new algorithm named as DP-ETSP is designed, where the real-time information propagation among agents is avoided. Additionally, under the proposed event-triggered mechanism, an analysis of mean-square consensus and optimality over time-varying directed networks is made when the added Laplace noises meet some specific decaying conditions. Convergence rate results are further established under a specific stepsize, which are equal to the rate of stochastic gradient-push algorithm without event-triggered communication. Moreover, the differential privacy preservation performance is analyzed and the rule for selecting privacy level is discussed. Finally, the feasibility and effectiveness of DP-ETSP are verified in two simulation cases.

During on-load starting process of an aviation wound-field synchronous starter/generator system, accurate rotor position information is required. Mechanical position sensor is susceptible to interference, increasing volume and weight, so online rotor position estimation is more desirable. Harmonics of main exciter (ME) caused by rotating rectifier are analyzed, and the fifth harmonic is used creatively to estimate rotor position in this article. In this method, by performing coordinate transformation on stator current of ME, rotor position increment is extracted and obtained through a low-pass filter. Meanwhile, taking advantage of the unidirectional conduction characteristics of rotating rectifier, a new idea to estimate initial rotor position is also proposed. In this approach, pulse signal is injected into the stator winding of main generator (MM) every fixed electrical angle, then the maximum and minimum current response correspond to that of MM's S and N pole respectively. Finally, combine initial rotor position and position increment, continuous rotor position of MM can be gained. The proposed methods avoid dependence on the saliency of MM, require no high-frequency signal injection and do not need secondary magnetic pole identification. Effectiveness and advantages of the proposed method are verified on the test.

The main generator (MG) and the main exciter (ME) are mounted on the same shaft in the brushless synchronous starter/generator (BSSG). Besides, the internal high-frequency signals, caused by the rotating rectifier, exist in the rotor windings of ME. These mechanical and electrical features of BSSG indicate that the sensorless starting control of MG could be conducted with ME. However, the existing research of this strategy is limited to extracting rotor position information from the steady-state characteristics of the rotor currents of ME and consequently has not fully exploited the potential. In this article, a dynamic sensorless starting control method of MG by using ME as a quasi-resolver is proposed. First, the injection mechanism of the excitation signals in the rotor of ME and the characteristics of the induced back electromotive force (EMF) in the stator of ME in different commutation modes are analyzed to clarify the dynamic operating principle of the quasi-resolver. Then, back EMF estimation based on extended state observer is presented and an envelope extraction method is proposed. According to the envelope features of the back EMF, a software-based resolver to digital conversion method is proposed. Finally, the effectiveness of this method is verified by experiments.

With the rapid development of more-electric aircrafts, integrated starter–generator (ISG) with less volume and weight has become the development trend in aircraft power system applications. Advantages of high reliability and excellent power generation quality make the brushless wound-rotor synchronous starter–generator (BLWRSSG) most attractive candidate for the ISG system in aircraft application. In this article, four key technologies to achieve a high-performance BLWRSSG are comprehensively reviewed, including 1) high-efficient brushless excitation technology, 2) high-performance starting control technology, 3) rotor position estimation technology, and 4) rotating rectifier fault diagnosis technology. In each key technology, the basic operation principle, merit and demerit, and application of different topologies or methods in the literature are discussed and compared in depth. This article contributes to a thorough understanding of operation principle and key technologies of the BLWRSSG system, and provides a reference to researchers and engineers involved in research of aircraft ISG system.

Herein, we describe a Pd-catalyzed [2+3] cycloaddition/cross-coupling reaction of allenyl acetates for the Z/Eselective and diastereoselective synthesis of dendralene-functionalized dihydrofurans. Remarkably, mechanistic studies show the formation of an epoxide from a carbonyl bond via cycloaddition, which is practically and mechanistically significant for the construction of other bioactive heterocyclic epoxides. This research also revealed the utility and potential of allenic esters as C2 synthons and 1,2-biselectrophiles in cycloaddition reactions.

This study addresses the stability and stabilization problems of discrete-time semi-Markov jump linear systems (S-MJLSs) with unavailable sojourn-time information. The sojourn-time probability mass functions (S-TPMFs) of discrete-time semi-Markov chains are no longer confined to the geometric distribution, and it is difficult to obtain accurate and comprehensive information for S-TPMFs in practice. This is because S-TPMFs are usually deduced from the statistical characteristics according to the sampled-data, while adequate samples are often costly and time consuming. In this study, when the S-TPMFs for semi-Markov chains are assumed to be unavailable, the σ-error mean square stability is investigated for discrete-time S-MJLSs with some widely used assumptions; for semi-Markov chains, only the transition probability matrix of the embedded chain is used. In addition, the existence conditions of the effective controller are provided for closed-loop systems without using the information of S-TPMFs. Numerical examples are presented to illustrate the validity of the obtained theoretical results.

Drug resistance caused by epidermal growth factor receptor (EGFR) mutation has largely limited the clinical use of EGFR tyrosine kinase inhibitors (EGFR-TKIs) for the treatment of non-small-cell lung cancer (NSCLC). Herein, to overcome the intractable problem of drug resistance, proteolysis targeting chimeras (PROTACs) targeting EGFR mutants were developed by optimizing covalent EGFR ligands. Covalent or reversible covalent pyrimidine- or purine-containing PROTACs were designed, synthesized, and evaluated. As a consequence, covalent PROTAC CP17, with a novel purine-containing EGFR ligand, was discovered as a highly potent degrader against EGFRL858R/T790Mand EGFRdel19, reaching the lowest DC50values among all reported EGFR-targeting PROTACs. Furthermore, CP17exhibited excellent cellular activity against the H1975 and HCC827 cell lines with high selectivity. Mechanism investigation indicated that the lysosome was involved in the degradation process. Importantly, the covalent binding strategy was proven to be an effective approach for the design of PROTACs targeting EGFRL858R/T790M, which laid the practical foundation for further development of potent EGFR-targeting PROTACs.

Mixed lineage leukemia (MLL) gene rearrangements are associated with acute leukemia. The protein menin is regarded as a critical oncogenic cofactor of the resulting MLL fusion proteins in acute leukemia. A direct interaction between menin and the MLL amino terminal sequences is necessary for MLL fusion protein-mediated leukemogenesis. Thus, inhibition of the interaction between menin and MLL has emerged as a novel therapeutic strategy. Recent improvements in structural biology and chemical reactivity have promoted the design and development of selective and potent menin–MLL interaction inhibitors. In this Perspective, different classes of menin–MLL interaction inhibitors are comprehensively summarized. Further research potential, challenges, and opportunities in the field are also discussed.

Objective: Atherosclerosis (AS), a chronic inflammatory disease, is the basis of cardiovascular disease (CVD). Although the treatment has been greatly improved, AS still imposes a large burden on human health and the medical system, and we still need to further study its pathogenesis. As a novel biomolecule, transfer RNA-derived fragments (tRFs) play a key role in the progression of various disease. However, whether tRFs contribute to atherosclerosis pathogenesis remains unexplored. Methods: With deep sequencing technology, the change of tRFs expression profiles in patients with AS compared to healthy control group was identified. The accuracy of the sequencing data was validated using RT qPCR. Subsequently, we predicted the potential target genes of tRFs by online miRNA target prediction algorithms. The potential functions of tRFs were evaluated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Results: There were 13 tRFs differentially expressed between patients with AS and healthy controls, of which 2 were up-regulated and 11 were down-regulated. Validation by RT-qPCR analysis confirmed the sequencing results, and tRF-Gly-GCC-009 was highly up-regulated in the AS group based on the results of sequencing which was confirmed by RT-qPCR analysis. Furthermore, GO enrichment and KEGG pathway analyses indicated that 10 signaling pathways were related to tRF-Gly-GCC-009. These pathways might be physiopathological fundamentals of AS, mainly involving in Apelin signaling, Notch signaling and calcium signaling. Conclusion: The results of our study provide important novel insight into the underlying pathogenesis and demonstrate that tRFs might be potential biomarkers and therapeutic targets for AS in the future.

Graphite carbon nitride (g-C3N4) is a common photocatalyst, but it only shows limited photocatalytic performance due to its inherent carrier recombination. Hence, a novel 1D/2D FeV3O8nanorod/g-C3N4nanosheet composite photocatalyst was synthesized. X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) confirmed that FeV3O8and g-C3N4were successfully coupled together and formed a clear and intimate interface. The optimized sample (FCN-10) exhibits superior performance for ibuprofen (IBF) degradation under visible light irradiation, and its kinetic rate constant is 4 times that of g-C3N4nanosheets. Based on the band energy structure, reaction oxide species (ROS) quenching experiments and single-particle photoluminescence data analysis, we considered that a Z-scheme heterojunction was generated in the FCN system. For the first time, the Fukui index (f−), the highest occupied molecular orbital (HOMO), and atoms-in-molecules (AIM) topological analysis were used to analyze the active sites and covalent bonds of IBF molecules that were susceptible to the attack of ROS during photocatalysis, and the results were in good agreement with the LC-MS/MS intermediate detection. In addition, the toxicity of the transformation products was evaluated by quantitative structure–activity relationship (QSAR) analysis, suggesting that the proposed photocatalytic technique was a green method.

Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process-safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging information technologies such as artificial intelligence (AI) are quite promising as a means of overcoming these difficulties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety; ② knowledge-based reasoning for process safety; ③ accurate fusion of heterogeneous data from various sources; and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context.

Objective To assess the clinical outcomes of donepezil plus memantine (DM) and donepezil (DO) alone in Asian patients with a concomitant diagnosis of moderate-to-severe Alzheimer’s disease and mild-to-moderate chronic obstructive pulmonary disease (AD-COPD).Methods We conducted a retrospective analysis of patients with AD-COPD who received either DM or DO for 6 months, or until the occurrence of unacceptable adverse events or disease progression, between June 2012 and May 2016. The primary endpoint was the score on the Standardized Mini-Mental State Examination (SMMSE). Secondary endpoints were scores on the caregiver-rated Bristol Activities of Daily Living Scale, Neuropsychiatric Inventory, Dementia Quality of Life (DEMQOL)-Proxy, and General Health Questionnaire 12.Results In total, 154 eligible patients received DM, whereas 156 received DO. Compared with patients who received DO, patients who received DM had significantly higher mean scores on the SMMSE by 2.1 points (95% confidence interval, 1.3–2.5). Significant between-group heterogeneity was not detected in outcomes over time. The benefits of treatment with DM were greater than those of treatment with DO, in terms of the primary endpoint. Significant differences were also detected in terms of secondary endpoints.Conclusion DM is more effective than DO alone for Asian patients with AD-COPD.

Objective This study was performed to compare the clinical outcomes of traditional three-dimensional (3D) printing technology and 3D printing mirror model technology in the treatment of isolated acetabular fractures.Methods Prospectively maintained databases were reviewed to retrospectively compare patients with an isolated acetabular fracture who were treated with traditional 3D printing technology (Group T) or 3D printing mirror model technology (Group M) from 2011 to 2017. In total, 146 advanced-age patients (146 hips) with an isolated acetabular fracture (Group T, n = 72; Group M, n = 74) were assessed for a mean follow-up period of 29 months (range, 24–34 months). The primary endpoint was the postoperative Harris hip score (HHS). The secondary endpoints were the operation time, intraoperative blood loss, fluoroscopy screening time, fracture reduction quality, and incidence of postoperative complications at the final follow-up.Results The HHS, operation time, intraoperative blood loss, fluoroscopy screening time, and incidence of postoperative complications were significantly different between the groups, with Group M showing superior clinical outcomes.Conclusion In patients with an isolated acetabular fracture, 3D printing mirror model technology might lead to more accurate and efficient treatment than traditional 3D printing technology.

Objective To analyse the incidence and baseline predictors of the left ventricular ejection fraction (LVEF) returning to normal after dilated cardiomyopathy (DCM) following intervention with standard anti-heart failure (HF) medication in postmenopausal women.Methods Data from consecutive postmenopausal women who were first diagnosed with DCM and received anti-HF treatment during 2011 to 2018 were prospectively retrieved. The study population was divided into the LVEF recovery (LVR) group and the LVEF unrecovered (LVU) group according to whether LVEF was > 50%. The primary endpoint was baseline predictors of LVEF returning to normal.Results LVEF returned to normal in 49.3% (210/426) of patients with DCM. LVEF was significantly higher in the LVR group than in the LVU group (57.4% ± 6.9% vs 44.2% ± 5.3%; hazard ratio 1.312, 95% confidence interval 1.015–1.726) at the final follow-up. High systolic pressure, a short history of HF, a short QRS interval, a small left ventricular end-diastolic diameter (LVEDd), and high LVEF at admission were independent predictors of LVEF returning to normal.Conclusions LVEF returning to normal in postmenopausal women with DCM who receive standard anti-HF treatment is associated with systolic pressure, a history of HF, QRS interval, LVEDd, LVEF at admission, and favourable outcome.

To deal with the indeterminacy of the renewable energy in power system, electrochemical energy storage system is a promising solution for improving the flexibility of grid. As lithium-ion (Li-ion) battery-based energy storage system (BESS) including electric vehicle (EV) will dominate this area, accurate and cost-efficient battery model becomes a fundamental task for the functionalities of energy management. Equivalent circuit model (ECM) has been treated as a good trade-off between complexity and accuracy for Li-ion batteries modeling. Meanwhile, the resistance and capacitance in ECM cannot be constant values considering the effects of state of charge (SOC), C-rate and temperature. Hence, extensive parameters identification methods have been proposed to adapt the ECM models to various operating conditions. Online parameter identification is often sensitive to the measurement noise from sensors, while offline methods can usually provide more reliable parameters due to the high-precision laboratory facilities and well-predefined procedures. In this thread, offline parameter identification can both initialize the battery model and act as a benchmark for online application. This work reviews and analyzes the parameter identification for Li-ion battery models in both frequency and time domains. Three typical offline identification methods are introduced as the benchmark method, and further validated on hybrid pulse power characterization (HPPC) test and different driving cycles. By analyzing the variations of the parameters and the modeling accuracy, the recommendations of those methods for real applications are given as a conclusion. The discussion and results in this research can benefit the BESS energy management and system design, and further help the popularization of the Li-ion battery in EV and smart grid.

A practically useful approach for the cross-dehydrogenative coupling of quinazolin-4-one with simple nonactivated alkanes is reported. The products were smoothly formed under mild reaction conditions, within short reaction time at ambient temperature. The formation of new Csp3-Csp2bonds occurred at the electron-poor C-2 position of quinazolin-4-one. The approach has the potential to be an important tool for the late-stage functionalization of advanced synthetic intermediates and may find many applications in medicinal chemistry.

BF3·OEt2-mediated cross-coupling of (SnMe3)2with aryl triazene offers a new strategy for the synthesis of aryl stannane. A variety of synthetically useful aryl trimethylstannanes were produced in moderate to good yields with this metal-free approach. One-pot sequential Stille cross-coupling with different aryl bromides provides a short entry to both symmetrical and unsymmetrical biaryl compounds.

Modeling and characterizing high-dimensional aerodynamic pressures, on the elevator in the hoistway, is very challenging. An accurate model is helpful to understand and analyze the pressure characteristics, which is a vital consideration in the design of a competitive elevator. The current full-order models are usually governed by the Navier–Stokes equations and have low computational efficiency. A reduced-order model is thus necessary to improve computational efficiency. This work aims at investigating two data-driven approaches, for modeling and characterizing the aerodynamic pressures, i.e., proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) that are able to extract temporal–spatial structures from the data. A three-dimensional (3D) model of the realistic elevator is first built and simulation data of the aerodynamic pressures during the motion of the elevator in the hoistway is generated via computational fluid dynamics (CFD). Then, POD and DMD are employed to analyze the simulation data. It is found that through clustering techniques and since there exist local aerodynamic pressure pulses during the operation of the elevator, the aerodynamic pressure on the elevator has some distinct patterns. Therefore, cluster-based POD and DMD are further employed in the analysis. The results demonstrate that the cluster-based POD and DMD can achieve lower reconstruction errors than POD and DMD.

The extensive use of nanomaterials in commercial products will lead to environmental contamination, which may cause serious health issues in the future. To date, limited scavengers have been available for the capture of these emerging nanopollutants from water. The aim of this work was to synthesize hybrid ternary co-polymer membrane-coated micrometer-sized carbon fiber aerogels (MCFAs) to remove emerging nanopollutants from water and to investigate the mechanisms involved. The MCFAs were fabricated by direct pyrolysis of cotton in an inert atmosphere. Post-modification with chitosan (CS) and dopamine–polyethylenimine (PEI) complex generated amine-coated MCFAs with porous textures, followed by protonation using diluted acid solution. The surface functional groups and morphologies of the ternary CS and dopamine–PEI co-coated MCFAs were systematically characterized. The as-obtained hybrid composite was successfully used for the removal of citrate-capped gold and silver nanoparticles from water. The equilibrium data were well fitted to the Langmuir isotherm model, with maximal adsorption capacities of 31.2 mg g−1(Au NPs) and 41.8 mg g−1(Ag NPs) at ambient temperature. The highest adsorption capacities reached 30.2 mg g−1(Au NPs) and 34.9 mg g−1(Ag NPs) at the equilibrium concentrations; these were very close to the maximum adsorption capacities of the monolayers.In addition, the adsorption of both nanoparticles on the as-prepared composite followed the pseudo-second-order kinetics model. Therefore, this work may pave the way for enhancing the properties of MCFAs for removal of nanopollutants from medical and/or industrial wastewaters.

In the present study, a series of new 6-benzamide containing 4-phenylquinazoline derivatives were designed and synthesized as PI3Kδ inhibitors. The preliminary SAR for this series of compounds was established. PI3Kδ inhibitory assay showed that most of the synthesized compounds achieved significant activity against PI3Kδ. Compound 12h was the most potent PI3Kδ inhibitor, displaying an IC50 value of 17 nM. These results reveal that the 6-benzamide containing 4-phenylquinazoline is an encouraging chemical substructure, deserving further structural exploration to identify novel and highly potent PI3Kδ inhibitors.

A dual position-sensitive-detector (PSD)-based unit can be used for angular measurements of a multi-degree-of-freedom measurement system and a laser interferometry-based sensing and tracking system. In order to ensure the precision of incident beam direction measurement for a PSD-based unit, model and autoreflection alignment methods for correction of PSD-based unit parameters are proposed. Experimental results demonstrate the deviations between the angular measurements obtained using a dual PSD-based unit and an autocollimator varied by 70″, 20″, and 1″ for three runs of the autoreflection alignment method, respectively, and the model method deviations all varied by 1″ in the 1000″ measurement range for three runs. It is therefore concluded that the model method is more reliable than the autoreflection alignment method for ensuring the accuracy of a dual PSD-based unit.

In this study, a kind of unique Fe2O3/Pt hybrid consisting of uniform platinum nanoparticles deposited on a nanoflake-shaped Fe2O3support was prepared by using a solvothermal reaction followed by a heat-induced reduction process. The prepared Fe2O3sample displays well-defined nanoflake-like morphology; remarkably, there are many specific cavities on its surface. In addition, uniform Pt nanoparticles with narrow size distribution were deposited onto the surface of the preformed flake-like Fe2O3support to form the Fe2O3/Pt hybrid via a facile heat-induced reduction reaction. Thus, the prepared Fe2O3/Pt hybrid can serve as heterogeneous catalyst over the hydrogenation reaction. Results demonstrated that the specific Fe2O3/Pt heterogeneous catalyst exhibits good catalytic performances, including high conversion, specific selectivity, and excellent recycling durability, over hydrogenation reactions for different substrates. Furthermore, the prepared Fe2O3/Pt heterogeneous catalyst could be easily separated from the product mixture by using a magnet and could be recycled for 10 cycles without catalytic activity loss. In a word, the present synthetic approach is facile, scalable, and reproducible, which can be easily facilitated to prepare other types of noble metals/metal oxide composite systems.