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IntroductionProlonged mechanical ventilation in intensive care units (ICUs) leads to increased morbidity, higher mortality rates, and elevated healthcare costs. Predicting successful weaning from mechanical ventilation with accuracy is essential for optimizing resource use and improving patient outcomes. The International Classification of Functioning, Disability and Health (ICF) framework offers a holistic perspective on health conditions and can be adapted to identify key predictors of weaning readiness. This study aims to develop a Delphi-based core predictor set for weaning in critically ill patients, utilizing the ICF model.Methods and analysisThe core predictor set development comprises three steps: (1) Literature review and expert consultation to gather weaning predictors, (2) Predictor alignment with ICF categories per established rules, and (3) Three-round Delphi survey with a multidisciplinary team. A systematic review across major databases will be conducted to identify predictors related to weaning predictors in critically ill adults from cohort studies, trials, and reviews. Predictors will then be categorized within ICF domains. A multidisciplinary expert panel will evaluate the relevance of each predictor using a 9-point Likert scale to achieve consensus.DiscussionThis study will contribute to the development of a standardized, evidence-based predictor set for weaning readiness in critically ill patients. Using the ICF framework, this study aims to encompass the complex factors that influence weaning, thereby enabling personalized care plans and improving weaning outcomes. The Delphi methodology guarantees a thorough, iterative process for building consensus by integrating diverse clinical perspectives.ConclusionThe proposed Delphi-based study protocol aims to establish a core set of predictors for weaning in the ICU setting, guided by the ICF model. Successful implementation of this predictor set could enhance decision-making around weaning trials, reduce unnecessary ventilation days, and ultimately improve patient outcomes and healthcare efficiency. Future validation and implementation studies will be essential to confirm the utility and generalizability of this predictor set in clinical practice.

Abstract Immune checkpoint inhibitor (ICI)-derived evolution offers a versatile means of developing novel immunotherapies that targets programmed death-ligand 1 (PD-L1)/programmed death-1 (PD-1) axis. However, one major challenge is T cell exhaustion, which contributes to low response rates in "cold" tumors. Herein, we introduce a fluorinated assembly system of LFNPs/siTOX complexes consisting of fluorinated EGCG (FEGCG), fluorinated aminolauric acid (LA), and fluorinated polyethylene glycol (PEG) to efficiently deliver small interfering RNA anti-TOX (thymus high mobility group box protein, TOX) for synergistic tumor cells and exhausted T cells regulation. Using a microfluidic approach, a library of LFNPs/siTOX complexes were prepared by altering the placement of the hydrophobe (LA), the surface PEGylation density, and the siTOX ratio. Among the different formulations tested, the lead formulation, LFNPs3-3/siTOX complexes, demonstrated enhanced siRNA complexation, sensitive drug release, improved stability and delivery efficacy, and acceptable biosafety. Upon administration by the intravenous injection, this formulation was able to evoke a robust immune response by inhibiting PD-L1 expression and mitigating T cell exhaustion. Overall, this study provides valuable insights into the fluorinated assembly and concomitant optimization of the EGCG-based delivery system. Furthermore, it offers a promising strategy for cancer immunotherapy, highlighting its potential in improving response rates in ‘‘cold’’ tumors. Graphical Abstract

Cognitive impairment is an important component of non motor symptoms in Parkinson's disease (PD), and if not addressed in a timely manner, it can easily progress to dementia. However, no effective method currently exists to completely prevent or reverse cognitive impairment associated with PD. We therefore aimed to investigate the therapeutic effect of near-infrared region II light (NIR-II) region illumination on cognitive impairment in PD through behavioral experiments (water maze and rotary rod) and multiple fluorescence immunohistochemistry techniques. The 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP)-induced group was compared with the MPTP- untreated rat group, showing a significant reduction in escape latency and significant increase in the fall latency in the MPTP-treated group. The horizontal analysis results indicated that NIR-II phototherapy improved the learning and cognitive abilities as well as coordination and balance abilities of rats. Post-treatment, the MPTP rats showed significantly shortened, escape latency, prolonged target quadrant residence time, and prolonged fall latency compared with pre-treatment. The longitudinal analysis results reaffirmed that NIR-II phototherapy improved the learning and cognitive abilities as well as coordination and balance abilities of rats. The multiple fluorescence immunohistochemistry analysis trend plot showed that the activated microglia and astrocytes in the hippocampus were highest in MPTP-induced PD untreated group, moderate in MPTP-induced PD treatment group, and lowest in the control group. Our data indicates that NIR-II illumination improves learning and cognitive impairment as well as coordination and balance abilities in PD rats by downregulating the activation of microglia and astrocytes in the hippocampus.

Rotated object detection in remote sensing images presents a highly challenging task due to the extensive fields of view and complex backgrounds. While Convolutional Neural Networks (CNNs) and Transformer networks have made progress in this area, there is still a lack of research on extracting and fusing features for small targets in complex backgrounds. To address this gap, we have extended the RTMDet framework by introducing three modules: the Focused Feature Context Aggregation Module, the Feature Context Information Enhancement Module, and the Multi-scale Feature Fusion Module. In the Focused Feature Context Aggregation Module, we replaced the Spatial Pyramid Pooling Bottleneck (SPPFBottleneck) to better extract small target features by focusing on contextual information. The Feature Context Information Enhancement Module enhances the model’s perception of multi-dimensional temporal and spatial information. Finally, we combined the original features with the fused ones to prevent the loss of specific features during the fusion process. Our proposed model, named the Multi-scale Feature Context Aggregation Network (MFCANet), was evaluated on four challenging remote sensing datasets (MAR20, SRSDD, HRSC, and DIOR-R). The experimental results demonstrate that our method outperforms baseline models, achieving improvements of 2.13%, 10.28%, 1.46%, and 1.13% in mAP for the MAR20, SRSDD, HRSC, and DIOR-R datasets, respectively.

As they are the core components of the drive motor in electric vehicles, the accurate fault diagnosis of rolling bearings is the key to ensuring the safe operation of electric vehicles. At present, intelligent diagnostic methods based on current signals (CSs) are widely used owing to the advantages of the easy collection, low cost, and non-invasiveness of CSs. However, in practical applications, the fault characteristics of the CS are weak, resulting in diagnostic performance that fails to meet the expected standards. In this paper, a diagnosis method is proposed to address this problem and enhance the diagnosis accuracy. Firstly, CSs from two phases are processed by periodic resampling to enhance data features, which are then fused through splicing operations. Subsequently, a feature enhancement module is constructed using multi-scale feature fusion for decomposing the input. Finally, a diagnosis model is constructed by using an improved channel attention module (CAM) for enhancing the diagnosis performance. The results from experiments containing two different types of bearing datasets show that the proposed method can extract high-quality fault features and improve the diagnosis accuracy, presenting great potential in intelligent fault diagnosis and the maintenance of electric vehicles.

Abstract Identifying travel modes from Global Navigation Satellite System (GNSS) trajectories is helpful for traffic management. In mode identification, the motion features are extracted from trajectories to train the classifiers. However, features would be distorted by the positioning noise when migrating existing frameworks to poor‐quality tracks. This study aims to answer how to eliminate the impact of positioning error on mode identification. Specifically, six widely used Trajectory Noise Reduction (TNR) methods were tested. Representative motion features were calculated and sent to several classical classifiers to evaluate the effect of TNR. Then, the extent to which TNR restores motion features is analysed by information gain. To verify the robustness of these methods, multiple noise scenarios are designed to simulate possible positioning noise. The results show that the trajectory smoothing methods perform better than the outlier elimination methods regardless of the type and magnitude of noise. In particular, the Gaussian kernel smoothing can achieve the highest effect in almost all noise scenarios. For untested TNR methods that require a time window radius parameter, a 30‐s time window is a good candidate. Moreover, the visualisation verification cannot ensure the best TNR method for travel mode identification.

In the field of session-based recommendation by anonymous sessions, the commonly used supervised learning modeling method has the problem of sub-optimal recommendation. The supervised reinforcement learning (SRL) recommendation framework can be used to solve this problem, but there is currently a lack of research on graph state representations of anonymous sessions in this field. In this regard, we propose a supervised reinforcement session recommendation model, HG-SRL, based on global hypergraphs and local session graphs. In this model, we propose, for the first time, a state representation method based on hypergraph neural networks and graph neural networks to bridge the gap in SRL in graph state construction methods. To fully utilize graph information at both global and local levels, we propose a self-matching attention fusion mechanism, which fuses the different levels of information contained in the two graphs through cross-calculation and then embeds them in the final graph state representation. To make the state more comprehensive, we also mine the neighboring sessions of each anonymous session on the global session hypergraph to supplement the neighboring session information of the anonymous session. Experimental tests were conducted on three real-world datasets, which have shown that HG-SRL can effectively improve the accuracy of session recommendations.

High-resolution multi-spectral (HRMS) images have been widely used in various fields, however, they can not be directly obtained due to the physical hardware limits of existing remote sensing satellites. Therefore, the pansharpening technique has been widely explored as an effective tool to generate HRMS images by fusing the complementary information of low-resolution multi-spectral (LRMS) images and high-resolution panchromatic (PAN) images. Existing deep learning-based pansharpening methods mainly focus on enhancing the spatial representation ability of the network, while paying little attention to modeling spectral dependencies in spite of its significance for remote sensing data. In this paper, we propose a simple yet effective channel group shuffling (CGS) module to explore the implicit relationships with regard to the adjacent and cross-channels while considering spatial information. To be specific, the proposed CGS module consists of two components: the channel group module and the feature shuffle fusion module. The former enhances the diversity of spectral information and cross-channel information communications while ensuring the spectral order of the input feature. The latter integrates the cross-group feature maps with rich spatial-spectral information. Equipped with the proposed functional module, our image fusion network, dubbed CGSNet, produces favorable results against existing state-of-the-art counterparts over various satellite datasets. Ablation studies further verify the flexibility and effectiveness of our core design.

In order to further reduce the torque, flux-linkage fluctuation, and current harmonic content of dual three-phase permanent magnet synchronous motors, this paper proposes a direct torque control strategy combined with a master–slave virtual vector duty cycle assignment. Two types of virtual voltage vectors with different amplitudes are used to form a harmonic suppression switching table. The virtual vectors are classified into master and slave virtual vectors according to the degree of influence on the torque and the flux-linkage. Then, the duty cycle of the master and slave virtual vectors is recalculated and allocated through the evaluation function to achieve accurate control of the torque and the flux-linkage. Finally, the switching sequences of the master and slave virtual vectors that act together in one control cycle are rearranged into a symmetrical waveform. It is experimentally verified that the phase current THD of the proposed strategy is reduced by 69.4%, the 5th and 7th current harmonics content is significantly reduced, and the torque fluctuation and flux-linkage fluctuation can also be effectively suppressed, which provides better dynamic performance and steady-state performance.

This research proposes a strategy to diagnose open-phase faults (OPF) and open-switching faults (OSF) in dual three-phase permanent magnet synchronous motor (DTP-PMSM) inverters. The method is based on the dual d–q predictive current model and involves establishing a mathematical model and utilizing the finite control set model predictive current extraction technique to predict the motor current. It then analyzes the characteristics of the switching-tube current under both normal and fault conditions. Finally, a fault predictive current model is introduced and the residual is calculated based on the predicted fault current value and the actual measured current value to diagnose the inverter fault. The proposed method effectively overcomes misjudgment issues encountered in traditional open-circuit fault diagnosis of inverters. It enhances the system’s response speed during dynamic processes and strengthens the robustness of diagnosis algorithm parameters. The experimental results demonstrate that the proposed method can rapidly, effectively, and accurately diagnose open-circuit faults presented in this paper fastest within one-fifth of a current cycle. It achieves a diagnostic accuracy rate of 97% in the dual three-phase permanent magnet synchronous motor drive system.

The application of sericin hydrogels is limited mainly due to their poor mechanical strength, tendency to be brittle and inconvenient sterilization. To address these challenges, a sericin hydrogel exhibiting outstanding physical and chemical properties along with cytocompatibility was prepared through crosslinking genipin with degraded sericin extracted from fibroin deficient silkworm cocoons by the high temperature and pressure method. Our reported sericin hydrogels possess good elasticity, injectability, and robust behaviors. The 8% sericin hydrogel can smoothly pass through a 16 G needle. While the 12% sericin hydrogel remains intact until its compression ratio reaches 70%, accompanied by a compression strength of 674 kPa. 12% sericin hydrogel produce a maximum stretch of 740%, with breaking strength and tensile modulus of 375 kPa and 477 kPa respectively. Besides that, the hydrogel system demonstrated remarkable cell-adhesive capabilities, effectively promoting cell attachment and, proliferation. Moreover, the swelling and degradation behaviors of the hydrogels are pH responsiveness. Sericin hydrogel releases drugs in a sustained manner. Furthermore, this study addresses the challenge of sterilizing sericin hydrogels (sterilization will inevitably lead to the destruction of their structures). In addition, it challenges the prior notion that sericin extracted under high temperature and pressure is difficult to directly cross-linked into a stable hydrogel. This developed hydrogel system in this study holds promise to be a new multifunctional platform expanding the application area scope of sericin.

Abstract Precisely reducing the size of metal-organic frameworks (MOFs) derivatives is an effective strategy to manipulate their phase engineering owing to size-dependent oxidation; however, the underlying relationship between the size of derivatives and phase engineering has not been clarified so far. Herein, a spatial confined growth strategy is proposed to encapsulate small-size MOFs derivatives into hollow carbon nanocages. It realizes that the hollow cavity shows a significant spatial confinement effect on the size of confined MOFs crystals and subsequently affects the dielectric polarization due to the phase hybridization with tunable coherent interfaces and heterojunctions owing to size-dependent oxidation motion, yielding to satisfied microwave attenuation with an optimal reflection loss of −50.6 dB and effective bandwidth of 6.6 GHz. Meanwhile, the effect of phase hybridization on dielectric polarization is deeply visualized, and the simulated calculation and electron holograms demonstrate that dielectric polarization is shown to be dominant dissipation mechanism in determining microwave absorption. This spatial confined growth strategy provides a versatile methodology for manipulating the size of MOFs derivatives and the understanding of size-dependent oxidation-induced phase hybridization offers a precise inspiration in optimizing dielectric polarization and microwave attenuation in theory.

Abstract Background The transition of the myometrium from a quiescent to a contractile state during labour is known to involve inflammation, which is characterized by the infiltration of immune cells and the secretion of cytokines. However, the specific cellular mechanisms underlying inflammation in the myometrium during human parturition are not yet fully understood. Methods Through the analysis of transcriptomics, proteomics, and cytokine arrays, the inflammation in the human myometrium during labour was revealed. By performing single‐cell RNA sequencing (scRNA‐seq) and spatiotemporal transcriptomic (ST) analyses on human myometrium in term in labour (TIL) and term in non‐labour (TNL), we established a comprehensive landscape of immune cells, their transcriptional characteristics, distribution, function and intercellular communications during labour. Histological staining, flow cytometry, and western blotting were applied to validate some results from scRNA‐seq and ST. Results Our analysis identified immune cell types, including monocytes, neutrophils, T cells, natural killer (NK) cells and B cells, present in the myometrium. TIL myometrium had a higher proportion of monocytes and neutrophils than TNL myometrium. Furthermore, the scRNA‐seq analysis showed an increase in M1 macrophages in TIL myometrium. CXCL8 expression was mainly observed in neutrophils and increased in TIL myometrium. CCL3 and CCL4 were principally expressed in M2 macrophages and neutrophils‐6, and decreased during labour; XCL1 and XCL2 were specifically expressed in NK cells, and decreased during labour. Analysis of cytokine receptor expression revealed an increase in IL1R2, which primarily expressed in neutrophils. Finally, we visualized the spatial proximity of representative cytokines, contraction‐associated genes, and corresponding receptors in ST to demonstrate their location within the myometrium. Conclusions Our analysis comprehensively revealed changes in immune cells, cytokines, and cytokine receptors during labour. It provided a valuable resource to detect and characterize inflammatory changes, yielding insights into the immune mechanisms underlying labour.

The switching frequency of high-power inverters, such as those used in rail transit traction systems, is low, due to switching loss and heat dissipation limitations. This can result in considerable output voltage harmonics. This paper proposes an optimal SPWM strategy for traction inverters based on non-equally spaced carriers to address this issue. By dividing the fundamental wave cycle into regions according to the principle of three-phase, half-wave, and quarter-wave symmetry, the carrier width is symmetrically changed in each region, and a switching angle sequence is generated by comparing the fundamental wave with the non-isometric carrier. The proposed optimal modulation strategy has lower harmonic content than traditional strategies within a specific modulation range. Enhancing the inverter output waveform leads to increased torque accuracy, lowering additional losses in the motor and avoiding overheating. This results in improved performance, enhanced efficiency, and extended service life of the motor system. To further reduce voltage harmonics across the full-speed range, a multi-mode segmented synchronous modulation strategy is designed based on the optimal modulation strategy for different modulation ranges. Appropriate switching points are selected to improve the stability of the traction drive system across the full-speed range. The effectiveness of the proposed method is verified through simulation and experimental results.

There is an urgent need to develop a low-cost and high-performance gas sensor for industrial production and daily life. Perovskite-type oxides are appropriate materials for resistive gas sensors. In this paper, two gas-sensing materials of gadolinium orthoferrite (GdFeO3) with rod and butterfly morphologies were obtained by annealing the corresponding precursors at 800 °C in a muffle furnace for 3 h. The precursors of GdFe(CN)6·4H2O with novel morphologies were prepared by a co-precipitation method at room temperature. The materials were evaluated in terms of their structure, morphology, and gas-sensing performance. The gas sensor based on GdFeO3 rods showed a better sensing performance than the sensor based on GdFeO3 butterflies. It exhibited the largest response value of 58.113 to 100 ppm n-propanol at a relatively low operating temperature of 140 °C, and the detection limit was 1 ppm. The results show that the GdFeO3 rods-based sensor performed well in detecting low concentration n-propanol. The satisfactory gas-sensing performance of the GdFeO3 rods-based sensor may be due to the porous structure and the large percentages of defect oxygen and adsorbed oxygen (37.5% and 14.6%) on the surface. This study broadens the application of GdFeO3 in the gas sensor area.

The maintenance of coordinated powerful episodic contractions of the uterus is the crucial factor for normal labor. The uterine contractility is gradually enhanced with the progression of labor, which is related to the gene expression of the myometrium. Competing endogenous RNA (ceRNA) can also regulate the gene expression. To better understand the role of ceRNA network in labor, transcriptome sequencing was performed on the myometrium of 17 parturients at different labor durations (0–24 h). From this, expression levels of mRNA, long non-coding RNA (lncRNA), circular RNA (circRNA), and microRNA (miRNA) were correlated with labor duration. Then, targeting relationships between mRNAs, lncRNAs, circRNAs, and miRNAs were predicted, and the ceRNA regulatory network was established. The mRNA expression patterns associated with cervical dilation and postpartum bleeding were further investigated. This analysis identified 932 RNAs positively correlated with labor duration (859 mRNAs, 28 lncRNAs, and 45 circRNAs) and 153 RNAs negatively correlated with labor duration (122 mRNAs, 28 lncRNAs, and 3 miRNAs). These mRNAs were involved in protein metabolism, transport, and cytoskeleton functions. According to the targeting relationship among these ceRNAs and mRNAs, a ceRNA network consisting of 3 miRNAs, 72 mRNAs, 2 circRNAs, and 1 lncRNA was established. In addition, two mRNA expression patterns were established using time-series analysis of mRNA expression in different phases of cervical dilation. A ceRNA network analysis for blood loss was performed; postpartum bleeding was closely related to inflammatory response, angiogenesis, and hemostasis. This study identified human myometrial transcriptome and established the ceRNA regulatory network depending on labor duration and highlighted the dynamic changes that occur at ceRNAs during parturition, which need to be considered more in the future to better understand how changes in gene expression are relevant to functional changes in human myometrium at labor.

Compared with other topologies, the modular multilevel converter (MMC) has the advantages of higher scalability and lower harmonic distortion. When carrier-based pulse-width modulation approaches are used for the MMC, the number of carriers increases for more sub-modules, and the complexity of the control and the memory required increases as a result. In addition, the synchronization of several carriers is another issue. Due to the unique constructional characteristics of the MMC, circulating currents will be generated internally, causing distortions in the arm currents and, thus, unnecessary converter losses. In this paper, an improved 2N+1 pulse-width modulation approach with low control complexity and a circulating current suppression strategy are proposed. Firstly, the conventional carrier phase-shifted 2N+1 pulse-width modulation approach is improved so that the number of carrier signals adopted in each arm is always two. Secondly, the redundant switching states are used to suppress the circulating current. Finally, the effectiveness of the proposed strategy is verified experimentally. The results show that the proposed method reduces the control complexity while retaining the output performance. Meanwhile, the circulating current can be suppressed.

The predictive current control method of permanent magnet synchronous motor has the advantages of fast dynamic response and easy digital implementation, so more attention has been paid to it. When the motor operates in a high-speed condition, the switching frequency is relatively low, the carrier ratio is low, and the rotor angle varies greatly within a control cycle, resulting in a large error in the traditional liner approximation prediction model and inaccuracy of the voltage control quantity calculation, which leads to the deterioration of the predictive current control effect. At the same time, the output harmonic of the three-phase current increases, which affects the stable operation of the motor. In this paper, we study the causes of the large errors in the prediction model based on the traditional linear approximation and phase current fluctuation of the permanent magnet synchronous motor under high speed and low carrier-ratio conditions. Based on the improvement of the prediction model and modulation, a new control strategy of variable switching frequency deadbeat predictive current control is proposed. The control method proposed in this paper improves the dynamic and steady-state performance of the motor, under the condition that the carrier ratio does not increase and reduces the fluctuation of the output current of the motor. Finally, the effectiveness and superiority of the proposed method are verified by an experiment.

To meet the requirements of output harmonic distortion of neutral point clamped (NPC) three-level inverter under low switching frequency conditions, multi-mode synchronous space vector modulation is usually adopted. When switching between different pulse patterns, there will be oscillation in the output current. This paper proposes a smooth switching method for synchronous space vector modulation. This method compensates the phase angle of the reference voltage vector, in order to make the flux trajectories continuous before and after switching. Multi-position smooth switching can be realized in the fundamental period, and there is no delay in switching. Compared with direct switching, the total harmonic distortion rate of current during switching is reduced. The calculation of the phase angle compensation value of the reference voltage vector is not affected by the specific parameters and operating conditions of the motor, and can be carried out offline. Finally, experiments are carried out on a 7.5 kW induction motor fed by NPC three level inverter to verify the feasibility and effectiveness of the proposed method.

ObjectiveThermal ablation is a minimally invasive procedure for the treatment of pulmonary malignancy, but the intraoperative measure of complete ablation of the tumor is mainly based on the subjective judgment of clinicians without quantitative criteria. This study aimed to develop and validate an intraoperative computed tomography (CT)-based radiomic nomogram to predict complete ablation of pulmonary malignancy.MethodsThis study enrolled 104 individual lesions from 92 patients with primary or metastatic pulmonary malignancies, which were randomly divided into training cohort (n=74) and verification cohort (n=30). Radiomics features were extracted from the original CT images when the study clinicians determined the completion of the ablation surgery. Minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) were adopted for the dimensionality reduction of high-dimensional data and feature selection. The prediction model was developed based on the radiomics signature combined with the independent clinical predictors by multiple logistic regression analysis. The area under the curve (AUC), accuracy, sensitivity, and specificity were calculated. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the predictive performance of the model. Decision curve analysis (DCA) was applied to estimate the clinical usefulness and net benefit of the nomogram for decision making.ResultsThirteen CT features were selected to construct radiomics prediction model, which exhibits good predictive performance for determination of complete ablation of pulmonary malignancy. The AUCs of a CT-based radiomics nomogram that integrated the radiomics signature and the clinical predictors were 0.88 (95% CI 0.80-0.96) in the training cohort and 0.87 (95% CI: 0.71–1.00) in the validation cohort, respectively. The radiomics nomogram was well calibrated in both the training and validation cohorts, and it was highly consistent with complete tumor ablation. DCA indicated that the nomogram was clinically useful.ConclusionA CT-based radiomics nomogram has good predictive value for determination of complete ablation of pulmonary malignancy intraoperatively, which can assist in decision-making.

A modular multilevel converter (MMC) can generate different common-mode voltage (CMV) values due to the high-frequency changing of the switching state under various modulation strategies. The high-frequency dv/dt will produce common-mode current in the equivalent common-mode loop to the ground, which will affect the insulation and shorten the life of the equipment. To eliminate the effect of common-mode voltage on MMC operation, a common-mode voltage elimination strategy (0CMV-SVPWM) is proposed for five-level MMC space vector pulse width modulation (SVPWM) by using the vector that does not generate common-mode voltage as the reference vector in this paper. The proposed strategy is studied and analyzed by the rapid prototype development experimental system based on RT-LAB to verify the feasibility and effectiveness of the proposed strategy.

The modular multilevel converter (MMC) has been widely used because of the advantages of easier expansion, lower harmonic distortion and higher output voltage level. If the MMC is adapted to high voltage application, more submodules need to be connected in series in each arm. Thus, the switching loss needs to be considered a key issue. A discontinuous modulation method with variable clamping interval width is proposed in this paper in order to reduce the switching loss under variable power factor conditions. Different widths of the clamping interval can be selected according to the requirements of the system. Meanwhile, the capacitor voltage ripple of the submodules can also be reduced. The feasibility and effectiveness of the proposed modulation method are verified under a RT-LAB rapid control prototype based MMC system.

The precision of deadbeat direct power control depends on the parameters of the system model. In wide frequency applications, such as multi- electric aircraft and electric vehicles, variations in frequency and resistive parameters will affect the control effect. The AC side voltage frequency of the generator rectifier varies widely, which will lead to a steady-state reactive power error in the deadbeat direct power control. In addition, the large temperature variation range during the operation of the multi-electric aircraft and electric vehicles leads to large changes in the filter inductance and line resistance of the AC side, and the model parameters do not match the actual parameters, which will further deteriorate the control accuracy. In this paper, a PWM rectifier control method is proposed for the occasions when the frequency and temperature change are in a wide range. Using repetitive control and power compensation, it solves the problems of steady-state reactive power error and control accuracy degradation caused by the mismatch of model parameters under severe operating conditions. The control method can precisely adjust the output DC voltage of PWM rectifier, and it also can maintain unity power factor and reduce the total harmonic distortion rate of the input current. The effectiveness of the proposed control method is verified by the experimental results.

This paper presents a new position sensorless control strategy for a brushless DC motor (BLDCM) driven by a four-switch three-phase inverter (FSTPI). This strategy introduces a flux-linkage function, which changes obviously at the time of the extremum jump. In the proposed strategy, the extremum jump edge determines the six commutation points needed for motor commutation. Then the high-precision and reliable commutation of the BLDCM is realized. This strategy can be used on BLDCM driven by FSTPI. Compared with other position sensorless control methods for BLDCM driven by FSTPI, the proposed method does not need to set a threshold value to detect the commutation point. It can obtain six commutation points required for motor commutation without interpolation. This avoids commutation errors caused by threshold value setting and interpolation. In addition, this strategy adopts a three-phase current control method for BLDCM driven by FSTPI. It can effectively restrain the current distortion of the capacitor middle point connection phase. And the terminal voltage is calculated. It can avoid the error caused by hardware sampling and improve the accuracy of the position sensorless control strategy. The experimental results verify the correctness of the theory and the effectiveness of the method.

The high-dynamic permanent magnet (PM) motor servo system with high-bandwidth is the core equipment for industrial production, and the control bandwidth is also an important indexes to evaluate the performance of the servo system. The non-cascaded direct predictive speed control is an appropriate scheme to optimize the dynamic performance of the PM motor servo system. However, the high bandwidth of the non-cascaded control structure results in poor anti-interference ability, and it cannot effectively deal with the coupling relationship between current and speed, leading to poor control performance in the current limit region. Regarding the above problems, a nonlinear predictive speed control strategy combined with harmonic disturbance observer is proposed. In the proposed strategy, the disturbances of the servo system are separated from the mathematical model according to the nonlinear modeling theory, and the traditional disturbance observer is modified to estimate the harmonics. A nonlinear control law with strong disturbance suppression ability was designed. Furthermore, a complete current and speed prediction mechanism was introduced into the algorithm, in which the proportional differential (PD) controller is employed as the connection medium between the reference current and speed to solve the coupling problem of the non-cascaded control structure.

For the neutral point clamped (NPC) three-level converter fed permanent magnet synchronous motor (PMSM) system, the performance of the conventional model predictive current control (MPCC) algorithm will be deteriorated if the amplitude of the neutral point potential (NPP) is large. Additionally, the adjustment process of the weighted coefficients of the conventional MPCC algorithm is complex because of numerous control terms in the cost function. To solve the above issues, an improved MPCC algorithm is proposed in this paper. Firstly, Newtonian iteration is used to transfer the stator current into stator voltage in the cost function. Then, the NPP term in the conventional cost function can be eliminated by introducing the partition control of the NP potential, which also eliminates the whole adjustment process of weighting coefficients. Finally, based on the amplitude of the NPP, the amplitude and phase angle of medium and small vectors are modified to improve the control performance of the torque and flux. Experimental results show that the fluctuation of the neutral point potential can be suppressed rapidly. Meanwhile, the performance of the torque, flux and current are also improved compared with the conventional MPCC.

In applications where motor inversion is forbidden, it is important to detect the initial rotor position of the motor. For this reason, based on coupling injection of high-frequency signal, a novel method of initial rotor position detection for brushless DC motors (BLDCM) is proposed in this paper. Firstly, the proposed method detects the relationship between three-phase winding inductances by injecting the high-frequency detection signal into motor windings in a coupling way, and the initial rotor position is determined into two sectors with 180 degrees electric angle difference. Then, the polarity of the permanent magnet rotor is determined by applying two opposite voltage vectors to motor windings, so that the initial rotor position is determined into a unique sector, and the positioning accuracy is 30 degrees electric angle. The proposed method significantly reduces the amplitude of the detection signal while increases its frequency by the way of coupling injection, thus reducing the response current and electromagnetic torque generated by the high-frequency signal and reducing the possibility of rotor inversion. Finally, the effectiveness of the proposed method is verified by experimental results.

Abstract Background Data are limited with regard to the relationship of albuminuria and major adverse cardiovascular events (MACE) in Chinese elder patients with high cardiovascular risk. Methods We did a retrospective cohort study using Chinese elder patients with high cardiovascular risks (n = 1474) to identify the association of albumin-to-creatinine ratio (ACR) and the incidence of MACE and all-cause mortality. Individuals were followed up from January, 2002 to November, 2007. The all-cause mortality and MACE, composite outcome of cardiovascular death, myocardial infarction, stroke and hospitalization of congestive heart failure were defined as primary endpoint. Results During the median following up of 56 months, 213 patients developed primary endpoint and 117 patients died. Patients with higher baseline urinary ACR (> 30 mg/g) experienced a nearly 2-fold of all-cause mortality and a 3-fold of heart failure hospitalization than those with lower baseline urinary ACR (≤10 mg/g).MACE, cardiovascular death, stoke and myocardial infarction showed no difference in three grades of urinary ACR (> 30 mg/g, 10 mg/g-30 mg/g, ≤10 mg/g) in this cohort. Patients above 65 years with increased ACR tended to experience higher mortality risks, and the association of increased ACR with higher hospitalization of congestive heart failure seemed to be more prominent in patients below 65 years than above 65 years. Conclusions In this post hoc analysis of Chinese individuals with high cardiovascular risks, higher urinary ACR was associated with higher all-cause mortality and heart failure hospitalization. Further studies are needed to find out whether there is age-specific ACR cutoff point.

This paper proposes a capacitor voltage offset suppression method based on reference voltage self-correction for a three-phase four-switch (TPFS) inverter-fed permanent magnet synchronous motor (PMSM) drive system to improve the motor control performance. Firstly, the αβ-axis reference voltage deviation caused by capacitor voltage offset is analyzed, and the relationship between the voltage to be compensated and the offset is obtained. Then, the capacitor voltage offset is calculated according to the motor speed, rotor position, current vector amplitude, and capacitance on the capacitor bridge arm of the TPFS inverter. Finally, the reference voltage is corrected according to the voltage to be compensated and the capacitor voltage offset. This method is simple and easy to implement, and there is no need to add voltage sensors or filters in the system to extract the capacitor voltage offset, and there is no complex parameter adjustment. The effectiveness of the proposed method is verified by experiments on a 20 kW interior permanent magnet synchronous motor.

In order to improve the position tracking precision of dual permanent magnet synchronous motor (PMSM) systems, a unified nonlinear predictive control (UNPC) strategy based on the unified modeling of two PMSM systems is proposed in this paper. Firstly, establishing a unified nonlinear model of the dual-PMSM system, which contains uncertain disturbances caused by parameters mismatch and external load changes. Then, the position contour error and tracking errors are regarded as the performance index inserted into the cost function, and the single-loop controller is obtained by optimizing the cost function. Meanwhile, the nonlinear disturbance observer is designed to estimate the uncertain disturbances, which is used for feed-forward compensation control. Finally, the proposed strategy is experimentally validated on two 2.3 kW permanent magnet synchronous motors, and the experimental results show that effectiveness and feasibility of proposed strategy.

Background and objective Lung cancer is the leading cause of cancer-related death in China. The results from a randomized controlled trial using annual low-dose computed tomography (LDCT) in specific high-risk groups demonstrated a 20% reduction in lung cancer mortality. The aim of tihs study is to establish the China National lung cancer screening guidelines for clinical practice. Methods The China lung cancer early detection and treatment expert group (CLCEDTEG) established the China National Lung Cancer Screening Guideline with multidisciplinary representation including 4 thoracic surgeons, 4 thoracic radiologists, 2 medical oncologists, 2 pulmonologists, 2 pathologist, and 2 epidemiologist. Members have engaged in interdisciplinary collaborations regarding lung cancer screening and clinical care of patients with at risk for lung cancer. The expert group reviewed the literature, including screening trials in the United States and Europe and China, and discussed local best clinical practices in the China. A consensus-based guidelines, China National Lung Cancer Screening Guideline (CNLCSG), was recommended by CLCEDTEG appointed by the National Health and Family Planning Commission, based on results of the National Lung Screening Trial, systematic review of evidence related to LDCT screening, and protocol of lung cancer screening program conducted in rural China. Results Annual lung cancer screening with LDCT is recommended for high risk individuals aged 50-74 years who have at least a 20 pack-year smoking history and who currently smoke or have quit within the past five years. Individualized decision making should be conducted before LDCT screening. LDCT screening also represents an opportunity to educate patients as to the health risks of smoking; thus, education should be integrated into the screening process in order to assist smoking cessation. Conclusion A lung cancer screening guideline is recommended for the high-risk population in China. Additional research , including LDCT combined with biomarkers, is needed to optimize the approach to low-dose CT screening in the future.

Acid rain (AR) adversely affects soybean growth and seed yield. However, genetic variation of soybean response to AR stress has not been well evaluated. Here, 441 cultivated soybean genotypes were subjected to simulated rainfall with either pH 4.2 (AR) or pH 5.6 (control) from the three-leaf stage to maturity in 2009 and 2010. After maturity, 14 traits potentially related to AR tolerance were determined. Analyses of variance showed that genetic variation in AR tolerance was statistically highly significant for all surveyed traits. Analysis of AR tolerance coefficients (ARTC) distinguished the 14 traits into four types. The Types I, II, and III variables were affected by AR stress to various degrees and displayed variations in AR sensitivity among genotypes with different sizes. Nevertheless, the Type IV variables were not influenced and showed little genetic variation. Among the three evaluation criteria for measuring AR tolerance of soybean genotypes, the ARTC and the ARTI (AR tolerance index) of seed yield were moderately associated, whereas the ARTC of seed yield and the average membership grade of ARTCs of the seven selected traits for comprehensive evaluating were strongly correlated. Applying the comprehensive evaluation method, 22 highly AR-tolerant and 23 highly AR-susceptible germplasms were identified. Seed yield changes after AR exposure of these screened genotypes were primarily attributed to changes in total pod number per plant, which consequently caused corresponding alterations in fruited pod number per plant and seed number per plant, and were secondarily due to changes in hundred seed weight. These novel germplasms will serve as materials for subsequent investigations aiming to explore the genetic mechanisms underlying AR tolerance and to develop AR-tolerant varieties in soybean.

In this work, we present a strategy to improve the gas-sensing performance of NiFe2O4 via a controllable annealing Ni/Fe precursor to fluffy NiFe2O4 nanosheet flowers. X-ray diffraction (XRD), a scanning electron microscope (SEM), nitrogen adsorption–desorption measurements and X-ray photoelectron spectroscopy (XPS) were used to characterize the crystal structure, morphology, specific surface area and surface structure. The gas-sensing performance was tested and the results demonstrate that the response was strongly influenced by the specific surface area and surface structure. The resultant NiFe2O4 nanosheet flowers with a heating rate of 8 °C min−1, which have a fluffier morphology and more oxygen vacancies in the surface, exhibited enhanced response and shortened response time toward ethanol. The easy approach facilitates the mass production of gas sensors based on bimetallic ferrites with high sensing performance via controlling the morphology and surface structure.

Discontinuous pulse width modulation (DPWM) strategies are usually adopted to reduce the switching loss and output current ripple of three-phase three-level traction inverters under three-phase load conditions. However, if there is a short circuit in any arbitrary phase or the inverter is used to feed a two-phase load, the output performance of conventional DPWM strategies will be deteriorated. Here, four improved DPWM (IDPWM) strategies for three-phase three-level neutral-point-clamped (NPC) traction inverter fed two-phase load are proposed. Unlike three-phase load conditions, the phase angle and the amplitude of each basic voltage vector in the space vector diagram are modified under two-phase load conditions. Consequently, sectors are re-divided and duty cycles of basic vectors during synthesis are recalculated. Clamping intervals of each phase for the four type discontinuous PWM (DPWM) strategies are rearranged according to the modified space vector diagram; then, the proposed DPWM strategies can be obtained. Compared with the conventional DPWM strategies, the output current waveform quality of the proposed strategy is significantly improved. Meanwhile, the amplitude of the neutral-point voltage ripple is also reduced.

Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm.

The band shapes and band positions of near-infrared (NIR) and Raman spectra change depending on the concentrations of specific chemical functionalities in a multicomponent system. To elucidate these effects in more detail and clarify their impact on the analytical measurement techniques and evaluation procedures, NIR transmission spectra and Raman spectra of two organic liquid three-component systems with variable compositions were analyzed by two different multivariate calibration procedures, partial least squares (PLS) and classical least-squares (CLS) regression. Furthermore, the effect of applying different concentration units (volume percent (%V) and weight percent (%W) on the performance of the two calibration procedures have been tested. While the mixtures of benzene/cyclohexane/ethylbenzene (system 1) can be regarded as a blended system with comparatively low molecular interactions, hydrogen bonding plays a dominant role in the blends of ethyl acetate/1-heptanol/1,4-dioxane (system 2). Whereas system 1 yielded equally good calibrations by PLS and CLS regression, for system 2 acceptable results were only obtained by PLS regression. Additionally, for both sample systems, Raman spectra generally led to lower calibration performance than NIR spectra. Finally, volume and weight percent concentration units yielded comparable results for both chemometric evaluation procedures.

Interior permanent magnet synchronous motors (IPMSMs) are usually used in electric vehicle drives and in other applications. In order to enlarge the speed range of IPMSMs, the flux-weakening control method is adopted. The traditional flux-weakening control strategy degrades the control performance because of parameter mismatches caused by variation of motor parameters. An improved uncertainty and disturbance estimator (UDE)-based flux-weakening control strategy is proposed for IPMSM drives in this paper. The parameter tuning method in the UDE-based control is improved. In addition, a flux-weakening adjusting factor is put forward to reduce the torque fluctuation when the operation point switches between the constant torque region and the flux-weakening region. This factor can be adjusted online by a lookup table. Finally, the validity of proposed method is verified by the simulation and experimental results. The results show that the proposed control strategy can effectively enhance the robustness of the system in the flux-weakening region, and make the system switch more smoothly between the constant torque region and the flux-weakening region.

An improved direct torque control with space-vector modulation (DTC-SVM) scheme is presented in this paper. In the conventional DTC-SVM scheme, torque control performance is affected by the load conditions, due to the inappropriate linearization of the relationship between the flux angle and electromagnetic torque. Different from the conventional method, a torque controller with load angle estimation (TC-LAE) is proposed and the change rate of torque is regulated according to the variation of the load conditions, which could ensure the rapidity and consistency of torque performance at different load conditions. Meanwhile, an online permanent magnet synchronous motor and maximum torque per ampere (PMSM-MTPA) operation strategy based on the fitting solving method is proposed instead of the traditional two-dimensional look-up table, and the reference value of flux amplitude is calculated online to meet the MTPA requirement with the proposed method. The improved strategy is applied on a 6 kW PMSM, and the simulation and experimental results verified the effectiveness and the feasibility of the proposed strategy.

This paper presents a sector subdivision based space vector pulse width modulation (SVPWM) strategy with reduced current ripple for a three-level inverter. Using the output current ripple theory, closed-form expressions of average current ripple vectors for both continuous and discontinuous switching sequences are derived. Based on the sector and triangle distributions of conventional SVPWM strategy, each triangle is further divided into three small-regions. Then the switching sequence with the lowest magnitude of the average current ripple vector is applied in every small-region, so that the advantages of continuous pulse width modulation (CPWM) and discontinuous pulse width modulation (DPWM) under different modulation index conditions are combined to reduce the current ripple in the whole modulation range. The output performance of the proposed strategy is compared with the conventional CPWM and DPWM strategy, and experimental results verify that the proposed strategy could reduce the current ripple of three-level inverters effectively.

This paper presents a commutation torque ripple suppression strategy for brushless DC motor (BLDCM) in the high-speed region, which considers the back electromotive force (back-EMF) variation during the commutation process. In the paper, the influence of actual back-EMF variation on the torque and outgoing phase current during the commutation process is analyzed. A modified smooth torque mechanism is then reconstructed considering the back-EMF variation, based on which a novel torque ripple suppression strategy is further designed. Compared with the traditional strategy which controls the chopping duty cycle relatively smoothly in the commutation process, the proposed strategy dynamically regulates the chopping duty cycle, which makes it show a gradual decrease. This strategy can suppress the commutation torque ripple even in a long commutation process, and broaden the speed range of the commutation torque ripple reduction. Under the experimental conditions of this paper, the proposed strategy can effectively reduce the commutation torque ripple in the high-speed region, and avoid the outgoing phase current cannot be reduced to zero. The experimental results verify the correctness of the theoretical analysis and the feasibility of the proposed strategy.

In the silkworm, metamorphosis and moulting are regulated by ecdysone hormone and juvenile hormone. The subject in the present study is a silkworm mutant that does not moult in the 2nd instar (nm2). Genetic analysis indicated that the nm2 mutation is controlled by a recessive gene and is homozygous lethal. Based on positional cloning, nm2 was located in a region approximately 275 kb on the 5th linkage group by eleven SSR polymorphism markers. In this specific range, according to the transcriptional expression of thirteen genes and cloning, the relative expression level of the BmCPG10 gene that encodes a cuticle protein was lower than the expression level of the wild-type gene. Moreover, this gene's structure differs from that of the wild-type gene: there is a deletion of 217 bp in its open reading frame, which resulted in a change in the protein it encoded. The BmCPG10 mRNA was detectable throughout silkworm development from the egg to the moth. This mRNA was low in the pre-moulting and moulting stages of each instar but was high in the gluttonous stage and in newly exuviated larvae. The BmCPG10 mRNA showed high expression levels in the epidermis, head and trachea, while the expression levels were low in the midgut, Malpighian tubule, prothoracic gland, haemolymph and ventral nerve cord. The ecdysone titre was determined by ELISA, and the results demonstrated that the ecdysone titre of nm2 larvae was lower than that of the wild-type larvae. The nm2 mutant could be rescued by feeding 20-hydroxyecdysone, cholesterol and 7-dehydrocholesterol (7dC), but the rescued nm2 only developed to the 4th instar and subsequently died. The moulting time of silkworms could be delayed by BmCPG10 RNAi. Thus, we speculated that the mutation of BmCPG10 was responsible for the silkworm mutant that did not moult in the 2nd instar.