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To guarantee safe switching of the expensive medium-voltage (MV) device with limited durability, the overcurrent protection scheme based on Rogowski coil current sensor (RCCS) is the promising method, featuring fast response and galvanic isolation. However, it is an inherent contradiction to achieve the RCCS with both high noise immunity and high-bandwidth capabilities. In addition, the nonideal dc and low-frequency characteristics of the integrator cause drift and droop errors. In this article, to address the aforementioned challenges, the broadband RCCS is developed and integrated into the overcurrent protection circuit for the MV SiC mosfet. The novel coil is designed based on the transmission line theory to overcome the constraints imposed by parasitic components on bandwidth. The proposed coil achieves an extra-high bandwidth of approximate 300 MHz with high mutual inductance and shielding layers for high noise immunity. Furthermore, the broadband integrator design method with low-frequency attenuation is proposed to eliminate drift and reduce droop errors significantly. Based on the developed RCCS, the proposed overcurrent protection circuit reacts to both the fault under load and hard switching fault rapidly and softly turns off the device within merely 200 ns. Comprehensive experiments demonstrate its exceptional potential in monitoring current and protecting the expensive MV devices.

Recently, Electrooculography-based Human-Computer Interaction (EOG-HCI) technology has gained widespread attention in industrial areas, including assistive robots, augmented reality in gaming, etc. However, as the fundamental step of EOG-HCI, accurate eye movement classification (EMC) still faces a significant challenge, where their constraints in extracting discriminative features limit the performance of most existing works. To address this issue, a Residual Self-Calibrated Network with Multi-Scale Channel Attention (RSCA), focusing on efficient feature extraction and enhancement is proposed. The RSCA network first employs three self-calibrated convolution blocks within a hierarchical residual framework to fully extract the discriminative multi-scale features. Then, a multi-scale channel attention module adaptively weights the learned features to screen out the discriminative representation by aggregating the multi-scale context information along the channel dimension, thus further boosting the performance. Comprehensive experiments were performed using 5 public datasets and 7 prevailing methods for comparative validation. The results confirm that the RSCA network outperforms all other methods significantly, establishing a state-of-the-art benchmark for EOG-based EMC. Furthermore, thorough ablation analyses confirm the effectiveness of the employed modules within the RSCA network, providing valuable insights for the design of EOG-based deep models.

Driven by advancements in the semiconductor technology, especially silicon carbide, numerous packaging designs have been developed to meet demands of various applications. Prior to the market release, the reliability of these power modules must be comprehensively assessed. The mechanical characterization is an essential measure to assess the reliability of the power module due to its direct relation to the power module failure. The mechanical distribution and differences, typically on the submicron scale, pose significant measurement challenges. Therefore, achieving accurate sampling of the mechanical information without compromising the functionality and integrity of the power module remains a relentless pursuit in the mechanical characterization. In this article, a comprehensive review of state-of-the-art methodologies for the mechanical characterization of the power module is presented, including both direct and noncontact methods. The deformation mechanisms and associated measurement challenges are analyzed. Various measurement techniques are systematically compared and their advantages and disadvantages are highlighted. In addition, the utilization of the mechanical data in existing applications is discussed, and potential future research directions are discussed. This review may provide insights into the future development and deployment of the power module.

The development of current sensors for wide-bandgap (WBG) applications consistently emphasizes high bandwidth, minimal invasiveness, and integration. Despite the meticulous design that enables current shunts to achieve excellent performance with high bandwidth and low parasitics, their inherent bulkiness remains a significant challenge for their integration into high-integrated applications that depend on the high switching speeds of WBG power devices. This study thoroughly investigates and uncovers the tradeoff faced by traditional current shunts in balancing miniaturization and high bandwidth. Building upon this understanding, the miniaturized current shunt (MiniShunt) concept is introduced to overcome inherent limitations and achieve both high performance and compact size. To realize this concept, a physical implementation that involves the high-density stacking of multiple coupled transmission lines is presented. Additionally, a thermal network model specifically for the proposed MiniShunt configuration is developed and a comprehensive thermal analysis methodology for the current shunts is established. By applying this methodology to finite element analysis, the thermal safe operating area for the MiniShunt can be determined, further providing valuable insights into its maximum static power dissipation and maximum energy loss. These findings contribute to the development of a highly compact 9 × 9-mm, 100-mΩ current shunt with an ultrahigh bandwidth of 3 GHz, near-zero parasitic inductance, and a maximum energy loss of 2.0 J at a reference temperature rise limit of 20 °C. Extensive experiments conducted in both the frequency and time domains serve to further validate the advantages of the MiniShunt in terms of its miniaturization, integration, ultrafast response, and low invasiveness for future high-integrated power electronics applications.

Enhanced insulation and superior thermal characteristics are crucial in advanced packaging for medium voltage (MV) silicon carbide (SiC) power modules. Nonetheless, the reduction in thermal resistance typically compromises insulation level due to the decreased number of insulation layers. In this paper, the forced fluorinated liquid cooling is proposed, whereby fluorinated liquid (3M FC-40) is directed into the power module, substituting silicone gel and diminishing thermal resistance. Through the utilization of forced fluorinated liquid cooling, a reduction of 21°C in junction temperature at full load is demonstrated in the experiment, compared to traditional water cooled power modules. Furthermore, there is a 35.6% reduction observed in the maximum temperature rise ΔTj. As dissipation power is transferred from the topside of the chip to the fluorinated liquid, the possibility of unlimited stacking of direct bonded copper (DBC) is enabled to lower the electrical field, thereby facilitating insulation at the chip bottom side without any worries regarding heightened thermal resistance. Forced fluorinated liquid cooling resulted in a 39°C reduction in the double-stacked DBC power module. Moreover, partial discharge (PD) detection under square wave revealed that the DBC immersed in the fluorinated liquid remains free from PD at 10 kV, a significantly higher threshold than observed with silicone gel. A higher partial discharge inception voltage (PDIV) is anticipated for double-stacked DBC when immersed in 3M FC-40. Thus, the forced fluorinated liquid cooling can be considered a promising solution for the next generation of MV SiC power modules.

Due to the inherent parasitic inductance and high switching speed, the SiC mosfet generally experience significant overvoltage and oscillation, reducing the voltage margin and causing substantial electromagnetic interference. To mitigate these challenges, a novel auxiliary circuit using the gate charge injection (GCI) concept is proposed in this article. The GCI circuit, assembled across the drain-gate of the SiC mosfet, injects charges into the gate during the overvoltage stage of the turn-off process, effectively reducing overvoltage and oscillation without affecting the turn-off speed. The mechanism of the proposed GCI circuit is meticulously analyzed interval by interval based on the cell structure of the SiC mosfet, and its parameters are designed and validated through the circuit simulation. Additionally, the proposed GCI circuit, comprising Si-RC and PiN diode die, is integrated into the SiC power module and assessed by the double pulse test and power cycling test. Experimental results show a 70% reduction in the transient overvoltage at 600 V/30 A and complete the oscillation elimination, with only a 3.4% increase in the switching loss. The GCI circuit does not affect the turn-on process, making it an effective and cost-competitive solution for suppressing the overvoltage and oscillation in the SiC power module.

There is increasing interest in using deep learning–based object recognition algorithms to automate the labeling of image data collected from marine surveys. However, underwater object detection is a particularly challenging problem due to changes in scattering and absorption of light, and spotty data collection efforts, which rarely capture the broad variability. Using deep learning–based object detection systems for long-term or multisite marine surveying is further complicated by shifting data distributions between training and testing stages. Using data from the 100 Island Challenge, we investigate how object detection performance is impacted by changes in site characteristics and imaging conditions. We demonstrate that the combined use of data augmentation and unsupervised domain adaptation techniques can mitigate performance drops in the presence of domain shift. The proposed methodologies are broadly applicable to observational data sets in marine and terrestrial environments where a single algorithm needs to adapt to and perform comparably across changing conditions.

For a more secure, anti-interference characterization of high-speed wide-bandgap (WBG) power devices, there is a growing need for galvanically isolated measurement methods with higher bandwidth and wider dynamic range. Among these techniques, the differential sensing method has gained attention due to its simplicity, cost-effectiveness, wide dynamic range, and floating measurement capability. Nevertheless, the limited bandwidth of the differential method remains a significant obstacle for characterizing ultrafast switching transients of WBG devices. This article highlights the significant bandwidth limitations encountered in the front-end high-voltage attenuation of the differential method, i.e., the parasitic effects of capacitive networks and the overlooked high-frequency transmission line effects. To address these limitations, the concept of transmission line voltage divider (TL-VD) is introduced, enabling the extension of the operating frequency range of the front-end high-voltage attenuation into the GHz level. To achieve this, four underlying matching principles regarding resistance, capacitance, inductance, and wave impedance are established, which are further simplified to three decoupled, mutually independent, and easily implementable matching objectives of resistance, wave impedance, and transmission line length. These contributions collectively result in the successful development of a ±2.0-kV differential voltage sensing system (DVSS) with an ultrahigh measurement bandwidth of 1.3 GHz and a common-mode rejection ratio of 48 dB at 100 MHz. The experimental comparisons with state-of-the-art commercial galvanically isolated products in both the frequency and time domains confirm the superior performance of the developed TL-VD-based DVSS.

Ultrasound (US) is a type of mechanical wave that is capable of transmitting energy through biological tissues. By utilization of various frequencies and intensities, it can elicit specific biological effects. US imaging (USI) technology has been continuously developed with the advantages of safety and the absence of radiation. The advancement of nanotechnology has led to the utilization of various nanomaterials composed of both organic and inorganic compounds as ultrasound contrast agents (UCAs). These UCAs enhance USI, enabling real-time monitoring, diagnosis, and treatment of diseases, thereby facilitating the widespread adoption of UCAs in precision medicine. In this review, we introduce various UCAs based on nanomaterials for USI. Their principles can be roughly divided into the following categories: carrying and transporting gases, endogenous gas production, and the structural characteristics of the nanomaterial itself. Furthermore, the synergistic benefits of US in conjunction with various imaging modalities and their combined application in disease monitoring and diagnosis are introduced. In addition, the challenges and prospects for the development of UCAs are also discussed.

The medium voltage (MV) silicon carbide (SiC) power modules hold significant promise as a route for the solid-state converters to achieve higher power density, higher switching frequency, and lower loss. However, the emergence of partial discharge (PD) in the MV SiC power modules has posed a formidable challenge to enhancing its nominal voltage. In this article, a comprehensive review and comparative analysis of characterization, mitigation, and detection of PD under the square wave excitation is proposed for MV SiC power modules. First, the mechanism, detriments, and characterization of the PD issue and electrical tree in the MV power module are insightfully demonstrated. Meanwhile, the challenges from the PD for the MV SiC power module are emphasized. Besides, the geometric modification of direct bonded copper (DBC) structures to mitigate the PD issue is reviewed in detail. The limitations of the customized DBC are analyzed, considering the cost, reliability, and thermal resistance. Additionally, advanced dielectric materials are introduced and categorized. It is indicated that the effectiveness of the new dielectric under the square wave excitation stress still needs further investigation. Meanwhile, the optical, electromagnetic, electrical, and ultrasound detection methods under square wave excitation are further reviewed to assess the PD behavior in the MV SiC power module. Finally, suggested future researches for MV SiC power module packaging are proposed, aiming to inspire new ideas to further promote the insulation level of the MV SiC power module.

Epithelial ovarian cancer is among the deadliest gynecological tumors worldwide. Clinical treatment usually consists of surgery and adjuvant chemo- and radiotherapies. Due to the high rate of recurrence and rapid development of drug resistance, the current focus of research is on finding effective natural products with minimal toxic side effects for treating epithelial ovarian tumors. Cannabidiol is among the most abundant cannabinoids and has a non-psychoactive effect compared to tetrahydrocannabinol, which is a key advantage for clinical application. Studies have shown that cannabidiol has antiproliferative, pro-apoptotic, cytotoxic, antiangiogenic, anti-inflammatory, and immunomodulatory properties. However, its therapeutic value for epithelial ovarian tumors remains unclear. This study aims to investigate the effects of cannabidiol on epithelial ovarian tumors and to elucidate the underlying mechanisms. The results showed that cannabidiol has a significant inhibitory effect on epithelial ovarian tumors. In vivoexperiments demonstrated that cannabidiol could inhibit tumor growth by modulating the intestinal microbiome and increasing the abundance of beneficial bacteria. Western blot assays showed that cannabidiol bound to EGFR/AKT/MMPs proteins and suppressed EGFR/AKT/MMPs expression in a dose-dependent manner. Network pharmacology and molecular docking results suggested that cannabidiol could affect the EGFR/AKT/MMPs signaling pathway.

Retinoblastoma (RB) is an aggressive tumor of the infant retina. However, the ineffective targeting of its theranostic agents results in poor imaging and therapeutic efficacy, which makes it difficult to identify and treat RB at an early stage. In order to improve the imaging and therapeutic efficacy, we constructed an RB-targeted artificial vesicle composite nanoparticle. In this study, the MnO2nanosponge (hMNs) was used as the core to absorb two fluorophore-modified DNAzymes to form the Dual/hMNs nanoparticle; after loaded with the artificial vesicle derived from human red blood cells, the RB-targeted DNA aptamers were modified on the surface, thus forming the Apt-EG@Dual/hMNs complex nanoparticle. The DNA aptamer endows this nanoparticle to target the nucleolin-overexpressed RB cell membrane specifically and enters cells via endocytosis. The nanoparticle could release fluorophore-modified DNAzymes and supplies Mn2+as a DNAzyme cofactor and a magnetic resonance imaging (MRI) agent. Subsequently, the DNAzymes can target two different mRNAs, thereby realizing fluorescence/MR bimodal imaging and dual-gene therapy. This study is expected to provide a reliable and valuable basis for ocular tumor theranostics.

Gaze estimation based on electrooculograms (EOGs) has been widely explored. However, the inter-subject variability of EOGs still leaves a significant challenge for practical applications. It contributes to performance degradation when handling inter-subject issues. In this paper, an unsupervised transfer learning approach with an adaptive reweighting and resampling (ARR) strategy to fully consider individual variability is proposed for EOG-based gaze angle estimation. It allows quantifying domain shifts by leveraging the source-target similarities, reweighting and resampling the source data to retain relevant instances and disregard irrelevant instances during adaptation. Specifically, our proposed methodology first assesses the domain shifts via decomposing transformation matrices, which are estimated between the training subjects (denoted as multi-source domains) and the test subject (denoted as target domain). Then, the multi-domain shifts are assigned as weighted indicators to resample the multi-source domains for model training. Comparative experiments with several prevailing transfer learning methods including CORrelation ALignment (CORAL), Geodesic Flow Kernel (GFK), Joint Distribution Adaptation (JDA), Transfer component analysis (TCA), and Balanced distribution adaption (BDA) using two different normalization processes were conducted on a realistic scenario across 18 subjects. Experimental results demonstrate that the ARR strategy can significantly improve performance (mean absolute error (MAE) reduction: 7.0%, root mean square error (RMSE) reduction: 6.3%), outperforming the prevailing methods. Besides, the impacts of data diversity and data size on ARR strategy are further investigated. It exhibits that data size is more important than data diversity for EOG-based gaze angle estimation, and also presents the benefits of the ARR strategy for dealing with practical scenarios.

Reducing the thermal resistance is vital for power modules. Thermal conducting paths are formed by heterogeneous layers for insulation, causing inevitably high thermal resistance. In this article, with the aid of direct metallization technology, a direct bonded copper (DBC)-free power module concept is proposed to achieve near-junction water cooling. A 55% reduction of thermal resistance is achieved by using a DBC-free power module instead of a DBC interface. Reliability analysis indicates that the DBC-free power module is sufficiently reliable in terms of mechanical stress, fatigue, and peel strength. The junction temperature of the DBC-free power module is experimentally compared to indirectly and directly water-cooled power modules with the DBC interface. The proposed near-junction water cooling method has effectively achieved reductions of 28 °C and 11 °C in junction temperature, respectively, under full load conditions when compared to the designs of indirectly and directly water-cooled power modules. The maximum junction temperature rise ΔTj of the indirectly water-cooled power module is reduced from 50 °C to 21 °C. The unlimited promise of direct metallization technology in 3-D packaging is also highlighted.

Hyperspectral image (HSI) and light detection and ranging (LiDAR) data are complementary to each other, which can be combined to improve the classification performance. However, existing deep network models do not sufficiently consider their complementarity to design the network structure and loss functions. Moreover, there lacks a hierarchical mutual-assistance learning mechanism that leverages the modality-shared features to enhance the modality-specific ones and vice versa. In view of these, we propose a novel height information guided hierarchical fusion-and-separation network (HFSNet) for joint classification of HSI and LiDAR data. HFSNet consists of three major components, i.e., dual-structure feature encoders (DSFEs), feature fusion-and-separation blocks (F2SBs), and an edge decoder (ED). Specifically, the transformer and convolutional neural network (CNN) are introduced in DSFEs to encode the spectral and spatial information of HSI and LiDAR data, respectively. In F2SBs, the deformable convolution-based height information guided fusion module (HIGFM) and the modality separation refinement module (MSRM) are proposed to sequentially extract modality-shared and modality-specific features. Additionally, the ED is incorporated into our model to predict the LiDAR edge map from the HSI feature to improve the model’s generalization ability. As such, the learned features from HSI and LiDAR data are deeply fused and mutually enhanced. Experiments on three benchmark datasets show the superiority of HFSNet to the state-of-the-art methods for jointly classifying HSI and LiDAR data with limited training samples.

Driver fatigue poses a significant safety risk in road transport, prompting heightened public awareness. Electroencephalogram (EEG), a key physiological signal for fatigue characterization, has garnered substantial interest and served as de facto gold standard. Existing EEG-based fatigue detection methods often utilize limited forehead lobe channels or the entire brain’s EEG signals, potentially leading to information loss or redundancy. This oversight neglects the crucial aspect of optimizing channels. Moreover, many studies prioritize augmenting model performance through additional subnetworks, neglecting refined features, deepening network, and creating overfitting. To address these gaps, this article introduces an attention-guided multiscale convolutional neural network (MSCNN-CAM) for driving fatigue detection, comprising a MSCNN and a channel attention mechanism (CAM) module. The MSCNN optimizes network depth, capturing richer temporal and frequency features. The CAM module supplements the MSCNN by emphasizing valuable information, exploring channel contributions, and assessing the impact of feature refinement on model performance. The proposed method demonstrates promising results on the public SEED-VIG dataset with an average root mean square error (RMSE) of 0.051 and an average correlation coefficient (COR) of 0.966 across 23 subjects, outperforming alternative approaches in driving fatigue detection. These findings show that our proposed method perform more effectively for driving fatigue detection based on EEG.

Motivated by the excellent advantages of high switching speed, low on-resistance, and high thermal conductivity, the wide bandgap (WBG) devices, including silicon carbide metal-oxide-semiconductor field-effect transistor and gallium nitride high electron mobility transistors, have received increasing attention. However, the high switching speed of WBG devices also brings more concerns and challenges for the dynamic test, which need to be clarified. Based on the questionnaire-based survey administered to engineers and researchers in both the power electronics industry and academia, the focuses and concerns of the dynamic test for WBG devices are investigated in this article. According to the professional background of respondents, the experience, focuses and concerns for the dynamic test of WBG devices are obtained. Subsequently, the correlation between designed questions is analyzed. It is concluded that the measurement probe has a critical effect on the confidence level of the test results, and needs to be improved in some key parameters, such as the bandwidth, common mode rejection ratio, cost, and consistency, to meet the demand of the dynamic test of WBG devices. In addition, the outcomes of this survey and future frameworks for the dynamic test of WBG devices are concluded, which provides a roadmap for researchers and industry professionals to tackle the challenges associated with the dynamic test of WBG devices.

The agile and safe transdomain in waves is a promising feature but the primary bottleneck of the hybrid aerial underwater vehicle (HAUV). In this article, the surfing algorithm is proposed for Nezha-mini, our predeveloped HAUV prototype, to search for the dynamic window facilitating takeoff in waves and avoiding hazardous waves. For the first time, the cross-domain window, i.e., the vehicle is at the wave crest and heading downstream, is characterized and defined through the vehicle-wave coupled dynamic model. The novel surfing algorithm consists of the gradient perceptron, time-limited momentum gradient search, heading server, and initial conditions. Nezha-mini senses, searches, and tracks the dynamic window in real-time, until the takeoff decisions are triggered. Numerical simulations and experiments in regular and irregular waves reveal the effectiveness of the algorithm. The vehicle maintains a healthy initial attitude and inaccessible wave disturbance during takeoff, thus alleviating the thrust distraction from stability recovery and uncertainty. The average transition time and energy cost are reduced by 59.2% and 26.1% compared with random takeoff cases, and the locomotion is smooth, graceful, and low-risk. The computation and cost are low as the algorithm only requires the basic flight controller and the data from the inertial measurement unit instead of the prior parameters of the HAUV and waves. In comparison with the adaptive robust controller, which resists wave disturbance directly, this article provides an enlightening strategy from the perspective of harnessing waves.

Up to now, impaired bone regeneration severely affects the healing of bone fractures, thus bringing tremendous suffering to patients. As a vital mediator between inflammatory response and bone regeneration, M2 macrophage-derived exosomes (M2-Exos) attenuate inflammation and promote tissue repair. However, due to a lack of specific targeting property, M2-Exos will be rapidly eliminated after systematic administration, thus compromising their effectiveness in promoting bone regeneration. To solve this hurdle, we initially harvested and characterized the pro-osteogenic properties of M2-Exos. A bone marrow mesenchymal stem cell (BMSC)-specific aptamer was synthesized and 3-way junction (3WJ) RNA nanoparticles were applied to conjugate the BMSC-specific aptamer and M2-Exos. In vitro assays revealed that M2-Exos bore the representative features of exosomes and significantly promoted the proliferation, migration, and osteogenic differentiation of BMSCs. 3WJ RNA nanoparticles-aptamer functionalized M2-Exos (3WJ-BMSCapt/M2-Exos) maintained the original physical characteristics of M2-Exos, but bore a high specific binding ability to BMSCs. Furthermore, when being systemically administered in the mice model with femoral bone fractures, these functionalized M2-Exos mainly accumulated at the bone fracture site with a slow release of exosomal cargo, thereby significantly accelerating the healing processes compared with the M2-Exos group. Our study indicated that the 3WJ-BMSCapt/M2-Exos with BMSCs targeting ability and controlled release would be a promising strategy to treat bone fractures.Graphical Abstract

Rogowski coil (RC) has been commonly employed in power electronics due to its benefits of galvanic isolation, high-current measurement capability, and simple integration. However, the bandwidth of RC is restricted to tens of megahertz because of the inextricable resonance issue caused by its self-inductance and parasitic capacitance. This limitation hinders the ability of the RC to measure fast current transients such as those of wide-bandgap (WBG) power devices. In this letter, the concept of transmission line RC (TL-RC) is proposed to address the limitations of inductance and capacitance. The design criteria of double-ended impedance matching are further derived to ensure optimal signal integrity of TL-RC at gigahertz levels. These two concepts jointly form the isolated current sensor design with a bandwidth exceeding 3 GHz. Comparative experiments confirm the ultrafast and isolated advantages of the TL-RC for the WBG applications.

Electronic paper (e‐paper) is a reflective display technology with unique advantages, such as bistability, low‐power consumption, and high ambient contrast ratio. These features make e‐paper a promising candidate for future Internet of Things applications. Among different technologies of e‐paper, electrophoretic display (EPD) is the most successful one for commercialization. However, the edge ghosting (also known as the fringing effect) still limits the performance of EPD. Herein, we established a model of particle dynamics of electrophoresis, simulated the edge ghosting of microcapsule EPD, analyzed the edge ghosting effect, and revealed the relationship between thicknesses, dielectric constants of the back binder layer, and the edge ghosting. Two EPD panels with different thicknesses of back binder layer were demonstrated, which verifies the accuracy of this simulation model. With the proposed model, many device mechanisms and product issues can be analyzed and illustrated, which is supposed to guide the researchers in optimizing the device structure design of EPD. We developed a particle dynamics model for electrophoresis, simulating microcapsule EPD's edge ghosting and its correlation with back binder layer thicknesses and dielectric constants. By demonstrating two EPD panels with different back binder layer thicknesses, our simulation confirmed the predicted trend.

Motivated by advances in semiconductor technology and policies from the government, the electric vehicle (EV) has become a promising solution to climate change worldwide. As the core component of the EV, the power module is expected to have high reliability. Considering the different field demands, the power module is generally driven by various pulsewidth modulation (PWM) schemes. However, how to assess and select the appropriate PWM scheme based on the specific field application is a knotty challenge. In this article, a new perspective from the dynamic deformation of the power module is proposed to evaluate various PWM schemes. Based on experimental results, the power loss of the power module is calibrated and applied to the finite element analysis (FEA) model to clarify the deformation mechanism. Besides, the deformation measurement platform with high resolution and accuracy based on the confocal sensor is customized. Comparative results demonstrate that the FEA simulation model presents high agreement with the experimental results in terms of the maximum temperature and overall deformation, which confirm the accuracy of the power loss model. Furthermore, the continuous PWMs (CPWMs) generate the highest temperature and deformation, while the discrete PWM2 (DPWM2) presents the lowest temperature and deformation. The hysteresis curve of the power module consisting of the temperature and deformation is observed. The DPWM2 shows a 53% reduction in the closed area of the hysteresis curve compared to CPWMs, which indicates that it causes the lowest damage degree to the power module. In addition, the experimental results of the partial deformation demonstrate that the DPWM2 also has the lowest partial deformation among various PWMs. Generally, the DPWM2 is recommended when the DPWMs are enabled in the high-speed region of the EV.

This article presents a novel rapidly-exploring adaptive sampling tree algorithm for adaptive sampling missions using a hybrid aerial underwater vehicle (HAUV) in an air–sea 3-D environment. This algorithm innovatively combines the tournament-based point selection sampling strategy, the information heuristic search process, and the framework of the rapidly-exploring random tree algorithm. Hence, the vehicle can be guided to a region of interest to scientists for sampling and generate a collision-free path for maximizing information collection by the HAUV under the constraints of environmental effects of currents or wind and a limited budget. The simulation results show that the fast search adaptive sampling tree algorithm has higher optimization performance, faster solution speed, and better stability than the rapidly-exploring information gathering tree algorithm and the particle swarm optimization algorithm.

Due to the increasing concern for the global climate problem, the electric vehicle has drawn considerable attention. The power module with high reliability is the key to the deployment and development of the electric vehicle. However, in-depth evaluations, such as the tedious power cycling, are generally required to verify the reliability of the power module prior to putting it into the field application. Therefore, to determine the failure mechanism and evaluate the reliability of the power module, the in situ full-field characterization with 3-D deformation under the field application is essential. Besides, the characterization results can also provide a reference for the finite element analysis (FEA) model and further assess the reliability of the power module. In this article, the deformation mechanism and multiphysics simulation of the power module are comprehensively studied. To achieve the 3-D full-field characterization of the deformation, the stereo digital image correlation methodology is proposed to measure the out-of-plane and in-plane deformation. Additionally, in order to validate the feasibility of the proposed method, an active power cycle test rig that periodically heats up the power module by its own dissipation losses is constituted by the introduction of a front-to-front converter. The experimental results show that the maximum deformation occurs on the central surface of the focused zone while the edge bears a minimum deformation. Comparative evaluation indicates that the maximal error between experimental and simulation results is within 5%, thus, enable the effectiveness of the FEA simulation model.

Owing to the low parasitic inductance, high power density, and excellent heat extraction performance, double-sided cooling (DSC) is regarded as a promising packaging solution for the silicon carbide (SiC) power module. Nevertheless, given the unclear failure mechanism and missed lifetime model, the reliability assessment and lifetime prediction of the DSC SiC power module remains a concern. Besides, the accelerated aging test generally used for the reliability assessment of the SiC power module is extremely time-consuming and costly. Therefore, the obstacles mentioned before limit the development and deployment of the DSC SiC power module. Aiming to fulfill these research gaps, based on the aging mechanism and failure criterion of packaging materials, the lifetime model of the DSC SiC power module is proposed in this paper. Comparative experiments show that the relative error of the FEA-dominated model is less than 6%. Moreover, the stress property and creep principle of the solder layer in SiC and Si power modules are assessed, respectively. Besides, the lifetime models of SiC and Si power modules applying different packaging materials are created. It is found that the lifetime of the DSC power module is twice that of the single-sided cooling (SSC) counterpart. Furthermore, applying the same packaging, the lifetime of the SiC power module decreases by 70% compared with the Si counterpart. In addition, the lifetime of the DSC SiC power module affected by different materials such as ceramic and spacer is studied in order to enhance its reliability.

Surface modification manipulates the application performance of materials, and thrombosis caused by material contact is a key risk factor of biomaterials failure in blood-contacting/implanting devices. Therefore, building a safe and effective hemocompatibility platform is still urgent. Owing to the unique properties of polyamidoamine (PAMAM) dendrimers, in this study, modified surfaces with varying dendrimer densities were interacted with elements maintaining blood homeostasis. These included the plasma proteins bovine serum albumin and fibrinogen, cells in blood (platelets and erythrocyte), as well as endothelial cells (ECs), and the objective was to evaluate the blood compatibility of the chosen materials. Whole blood test and dynamic blood circulation experiment by the arteriovenous shunt mode of rabbit were also conducted, based on the complexity and fluidity of blood. The PAMAM-modified substrates, particularly that with a high density of PAMAM (N1.0), adsorbed proteins with lessened fibrinogen adsorption, reduced platelet activation and aggregation, and suppressed clotting in whole blood and dynamic blood testing. Furthermore, the designed PAMAM dendrimer densities were safe and showed negligible erythrocyte lysis. Concurrently, PAMAM modification could maintain EC growth and did not trigger the release of procoagulant factors. These results suggest that the PAMAM-modified materials are compatible for maintaining blood homeostasis. Thus, PAMAM dendrimers can work as excellent surface modifiers for constructing a hemocompatibility platform and even a primer layer for desired functional design, promoting the service performance of blood-contacting devices.

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In this study, a method was developed to form C(sp3)–C(sp2) bonds viacopper catalyst-promoted cross coupling of 2-methylquinoline and in-situ-activated 3-haloisoquinoline under mild conditions. The multi-component tandem reaction was used to construct new C–N, C=O and C–C bonds in one pot viasequential functionalization of the N1, C3 and C1 positions of 3-haloisoquinoline. This method can be used to efficiently access 1,2-disubstituted isoquinolinones by the three-component reaction of 3-halogen isoquinoline, alkyl halide, and 2-methylquinoline.

A model of particles dynamics of electrophoretic display was established to simulate the distribution of charged particles, edge ghosting effect with different thicknesses, dielectric constants of back binder layer. Reflectivities corresponding to particles distributions were simulated, which evaluated the extent of edge ghosting. The model can suggest the best values of the above parameters.

A model of particles dynamics of electrophoretic display was established to simulate the distribution of charged particles, edge ghosting effect with different thicknesses, dielectric constants of back binder layer. Reflectivities corresponding to particles distributions were simulated, which evaluated the extent of edge ghosting. The model can suggest the best values of the above parameters.

An iridium-catalyzed hydrogen transfer strategy, enabling straightforward access to tetrahydropyridine derivatives from aryl-1,8-naphthyridines and indolines was developed. This method has unprecedented advantages, including high step economy. In addition, it does not produce any byproducts or require an external high-pressure H2gas source. The method offers an important platform for the transformation of 1,8-naphthyridines and indolines into functionalized products.

Grand canonical Monte Carlo simulations combined with molecular dynamics (MD) simulations and density functional theory calculations are used to study the adsorption and separation potentials of surface-functionalized nanoporous carbons (NPCR, R = /N, /NB, −NH2, and −OH) for ethanol and benzene at 293 K. The surface-functionalized NPCs present a higher ethanol uptake (maximum = 5.61 mmol/g at 0.002 kPa) at a lower pressure range for their remarkable electrostatic affinity and strong electrostatic interaction (hydrogen bonding interaction) with ethanol. The MD simulation shows that surface modification enhances the ethanol molecular clustering effect under a pore occupancy less than 0.6, which further improves the ethanol adsorption performance. There is, however, no direct evidence that surface functionalization can enhance the benzene uptake by NPCs. Specifically, among the surface-functionalized NPCs, NPC/NB exhibits the highest ethanol/benzene selectivity under the entire pressure range (∼3.8 at 0.002 kPa and ∼8.6 at 10 kPa). Furthermore, NPC/NB and NPC/N have a better ethanol/benzene separation performance than NPC-NH2and NPC-OH. Electrostatic potential analysis shows that heteroatom doping impels the ethanol molecule cluster on surface graphite layers, which inhibits the benzene adsorption capacity of NPC/N and NPC/NB in the process of mixture adsorption. This study provides a possible strategy in the preparation of NPC for the ethanol/benzene mixture adsorptive separation.

Developing an adsorbent with high adsorption capacity and high selectivity is of great importance for the post-combustion CO2capture. Inspired by the theoretical calculation findings that the introduction of alkali metal atoms (e.g., Li, Na, and K) into the carbon framework can significantly increase the CO2adsorption capacity through the enhanced electrostatic interaction, herein, we have successfully developed a series of alkali metal doped carbons through a simple and effective strategy. The systematic characterization results prove that alkali metals are uniformly introduced into the carbon framework without changing the pore size distribution and amorphous structure of the original material, but slightly reducing the specific surface area. The adsorption performances from the static adsorption and the dynamic breakthrough experiments with a binary mixture of CO2/N2(15/85, v/v) reveal that the doping of alkali metals can greatly enhance the capture and separation of CO2, in which the lithium-doped porous carbon presents the best CO2uptake of 4.1 mmol/g at 25 °C (48.3% higher than that of undoped carbon) with the highest CO2/N2selectivity of 47 and fastest adsorption rate. The high adsorption capacity and selectivity presented are comparable to the data reported in the previous literature. The density functional theory and grand canonical Monte Carlo molecular simulation results demonstrate that, compared with N2, alkali metal doped carbon has a stronger binding energy and higher adsorption density for CO2and thus increases the CO2/N2selectivity to a greater extent. This proof-of-concept work paves an alternative way for the development of high-performance CO2adsorbents.

Salmonellais considered one of the leading causes for foodborne diseases in humans. Pork and its products contaminated with Salmonellaare increasingly recognized as an important source of human salmonellosis. The aim of this study was to investigate the antimicrobial resistance and prevalence of integrons in Salmonellaisolates from pig farms. In total, 92 of 724 (12.7%) samples were Salmonella-positive, including 64 (15.0%) from fecal samples, 27 (12.6%) from floor samples, 1 (4.5%) from water samples, and 0 from feed and air samples. These isolates showed the highest resistance to tetracycline (85.9%), followed by trimethoprim (67.4%), ampicillin (60.9%), and chloramphenicol (51.1%). In addition, 51 isolates carried the complete class 1 integron, most of which (42/51) harbored antibiotic resistance cassettes. A total of six gene cassettes including orfF, est-X, dfrA1+aadA1, aadA1, dfrA12+aadA2, and satwere identified, in which the most prevalent one was orfF(29.4%). Furthermore, all 19 class 1 integron-positive isolates harboring dfrgenes showed resistance to trimethoprim (SXT), suggesting that the trimethoprim resistance gene (dfr) may contribute to the emergence of SXT resistance phenotype. Therefore, considering the significance of integrons and related resistance genes for public health, special measures should be taken to control Salmonellaspp. on the pig farms and to prevent spread of integrons and associated resistance genes.

A flexible and robust microporous copper(II) metal–organic framework (MOF) based on a methyl-functionalized ligand, namely, [Cu3(μ3-OH)2(L)2(DMF)] (LIFM-ZZ-1; L = 2,2′-dimethyl-4,4′-biphenyldicarboxylic acid and DMF = N,N-dimethylformamide), was constructed. Its sorption performance for the separation of CH4, C2H6, and C3H8was investigated. LIFM-ZZ-1 showed a breathing behavior that led to a transition between large- and narrow-pore states. The sample also showed outstanding water stability. Gas adsorption experiments revealed that desolvated LIFM-ZZ-1 exhibited higher adsorption capacities for C2H6and C3H8(2.80 and 4.06 mmol·g–1) than for CH4(0.39 mmol·g–1) at 298 K and 1 bar. Breakthrough experiments showed that a CH4/C2H6/C3H8mixture was completely separated at 298 K, demonstrating the promising potential applications of this material for separating low contents of C2/C3 hydrocarbons from natural gas.

Owing to the unique features of electronic ink displays, including the bistability, paper‐like appearance, and sunlight visibility, electronic ink displays have been applied in many Internet of Things (IoT) fields. We reviewed mechanisms that have been proposed to be essential for electro‐optical behavior of electronic ink displays. This review might facilitate beginners to start their research in electronic ink studies. Owing to the unique features of electrophoretic E‐ink displays, including the bistability, paper‐like appearance, and sunlight visibility, E‐ink displays have been applied in many Internet of Things (IoT) fields. We summarized the mechanisms frequently used while designing the E‐ink displays, which might facilitate the new beginners to start their research in E‐ink fields.

High entropy alloy nanoparticles (HEA-NPs) are expanding their influence in many fields. To explore the electronic structures in such multielemental systems, HEA-NPs were synthesized on two different carbon substrates through carbothermal shock and in situreduction methods. The relationship between the apparent core level energy shifts (negative or positive) and the electron density changes among the components of quinary-metal HEA-NPs was investigated by X-ray photoelectron spectroscopy (XPS) analysis and first-principles electronic structure calculations. It was found that Cu displays a negative core level shift while Fe, Co, Mg, Cr, and Mn display a positive core level shift. While experiments show an apparent positive core level shift for Ni, electronic structure calculations reveal that this arises from shifts in the Fermi level and that the electron density redistribution in Ni behaves more like Cu than the other elements. The findings show that the electron density redistribution in the NPs occurs from less electronegative elements to more electronegative ones. This work should guide the design of HEA-NPs to expand their potential applications in mechanical structures, medicine, catalysis, and energy storage/conversion.

A flexible–robust copper(II) metal–organic framework, denoted as LIFM-100, has been successfully synthesized using a fluorinated linear dicarboxylate to link copper ions. LIFM-100 exhibits a breathing effect, which can transform reversibly between a large form (lp) and a narrow form (np) from single crystal to single crystal. In addition, LIFM-100 shows good thermal and chemical stability. By the introduction of trifluoromethyl functional groups and uncoordinated carboxyl acids, LIFM-100 features a good CO2/R22 adsorption/separation performance at 298 K, showing potential in natural gas purification and CO2/R22 capture.

IGF2BP3 (also known as IMP3, KOC), a member of the insulin-like growth factor mRNA-binding protein family (IMPs), has been a research target in recent studies of promoting embryo development and exacerbating cancer. IGF2BP3 is ubiquitously expressed in early embryogenesis stages but limited in postembryonic stages, which is important in many physiological aspects such as stem cell renewal, morphological development and metabolism. A large number of studies show that IGF2BP3 interacts with many kinds of non-coding RNAs and proteins to promote cancer cell proliferation and metastasis and inhibit cancer cell apoptosis. As IGF2BP3 is highly expressed in advanced cancers and associated with poor overall survival rates of patients, it may be a potential molecular marker in cancer diagnosis for the detection of cancerous tissues and an indicator of cancer stages. Therefore, anti-IGF2BP3 drugs or monoclonal antibodies are expected as new therapeutic methods in cancer treatment. This review summarizes recent findings among IGF2BP3, RNA and proteins in cancer processes, with a focus on its cancer-promoting mechanisms and potential application as a new biomarker for cancer diagnosis and treatment.

Thrombospondin-1, an extracellular matrix protein, is the first identified natural angiogenesis inhibitor. Thrombospondin-1 participates in a great number of physiological and pathological processes, including cell-cell and cell-matrix interactions via a number of cell receptors, including CD36 and CD47, which plays a vital role in mediating inflammation and performs a promoting effect in pulmonary arterial vasculopathy and diabetes. Thrombospondin-1 consists of six domains, which combine with different molecules and participate in various functions in cancers, serving as a critical member in diverse pathways in cancers. Thrombospondin-1 works as a cancer promotor in some pathways but as a cancer suppressor in others, which makes it highly possible that its erroneous functioning might lead to opposite effects. Therefore, subdividing the roles of thrombospondin-1 and distinguishing them in cancers are necessary. Complex structure and multiple roles take disadvantage of the research and application of thrombospondin-1. Compared with the whole thrombospondin-1 protein, each thrombospondin- 1 active peptide performs an uncomplicated structure and, nevertheless, a specific role. In other words, various thrombospondin-1 active peptides may function differently. For instance, thrombospondin-1 could both promote and inhibit glioblastoma, which is significantly inhibited by the three type I repeats, a thrombospondin-1 active peptide but promoted by the fragment 167-569, a thrombospondin-1 active peptide consisting of the procollagen homology domain and the three type I repeats. Further studies of the functions of thrombospondin-1 active peptides and applying them reasonably are necessary. In addition to mediating cancerogenesis, thrombospondin-1 is also affected by cancer development, as reflected by its expression in plasma and the cancer tissue. Therefore, thrombospondin-1 may be a potential biomarker for pre-clinical and clinical application. This review summarizes findings on the multiple roles of thrombospondin-1 in cancer processes, with a focus on its use as a potential therapeutic target.

As a widely used industrial material, the recovery of volatile organic compounds (VOCs) has great economic value and environmental significance. Improving the desorption performance of modified activated carbon in treating volatile organic compounds emissions is the key to the utilization of adsorbent and the recovery of adsorbate. In this study, five kinds of activated carbons and acetone were selected for orthogonal experiments to analyze the effect of multi-factors on the performances of major concern in engineering. The desorption process was divided into three zones, concentration fast rise zone, concentration fast decay zone and concentration slow decay zone, and quantitively evaluated for each zone. The results show that the enrichment ratio of SC800 is the highest in these sample, can reach 5.16, which is mainly affected by the chemical functional group with the highest adsorption energy, and is negatively correlated with the specific surface area. Combined the kinetic analysis and the quantitative evaluation of the total effects of chemical functional groups, the desorption rates are mainly related to the adsorbent surface saturation in the concentration fast decay zone and the total chemical effect in the concentration slow decay zone. In addition, the PC500 has the highest desorption efficiency of 69 %, which can be measured by the desorption activation energy.

Currently, advanced biomaterial design solutions often have more than two kinds of nanotechnology design strategies, but there is no suitable classification to describe these designs systematically. Based on the material design ideas and the modes of implementing functions, this article exemplifies and proposes a new nanotechnology classification that includes physical properties, the chemical reactions that respond to the microenvironment and bio-inspired incorporation. If two or more nanotechnology designs in the same classification are to be integrated into the same biological material, it is necessary to analyze the integration conflict between the designs. With the development of big data, this classification method may help researchers and artificial intelligence to realize automated integration of multiple designs and provide new material nanotechnology design integration solutions.

The cobalt carbide (Co2C) innovatively prepared from Co–Mn layered double hydroxide (CoMn LDH) has been investigated and evaluated toward its alternative synthesis conditions and different catalytic performances. Along with various characterization techniques, the preparation basically contains four steps (synthesis of CoMn LDH, calcination, reduction, and crystallization) that transform CoMn LDH to CoMn spinel and then to Co2C. Catalyst evaluation toward toluene pyrolysis was conducted. The sample with Co2C exhibited almost 100% conversion rate of toluene, where the resulting hydrogen yield (∼1.8%) is 6 times more than that of the blank test by using silica sand (∼0.3%), realizing the full transfer of hydrogen element from toluene to hydrogen molecule. Furthermore, based on the textural analysis and density functional dispersion correction calculation, which theoretically explained the easy accessibility of toluene to the crystal surface of Co2C(001) with a relatively high adsorption energy (about −280 kJ mol–1), it suggested that Co2C may expand more extensive applications in the field of catalysis.

We herein describe a practical direct amination of phenols through a palladium-catalyzed hydrogen-transfer-mediated activation method to synthesize the secondary and tertiary amines. In this conversion, environmentally friendly water and inexpensive ammonium formate were used as solvent and reductant, respectively. A range of amines, including aliphatic amines, aniline, secondary amines, and diamines, could be coupled effectively by this method to achieve mono/dual amination and cyclization of phenols. This study not only provides a green and mild strategy for the synthesis of secondary and tertiary naphthylamines but also expands the synthesis of chloroquine in organic chemistry.

The capture and separation properties of surface-functionalized activated carbons (AC–Rs, R= −COOH, −OH, −NH2, and −SO3H) for the methanol–acetone mixture were investigated for the first time by grand canonical Monte Carlo simulation (GCMC) and density functional theory (DFT). The effects of surface functional groups and structural characteristics of AC–Rs on the adsorption and separation behaviors of methanol and acetone were clarified. The surface functional group with strong electron-donating or electron-accepting capacity (i.e., −NH2, −OH, and −SO3H) was a crucial factor for the methanol–acetone capture and separation performance at the lower pressure range, and the accessible surface area was found to be another determinative factor. AC–NH2with the relatively large accessible surface area (4497 m2/g) exhibited an efficient capture performance for the single component (15.7 mol/kg for methanol and 6.7 mol/kg for acetone) and the highest methanol/acetone selectivity (∼23) at 0.02 kPa. At high pressures, the surface functionalization and available pore volume of AC–Rs played pivotal roles in the adsorptive separation process. This study provided mechanistic insights on how the surface functional groups affected the capture and separation properties of ACs, which would further provide a rational alternative strategy in the preparation and synthesis of ACs for the effective gas mixture separation.

The nature of diode reverse recovery is analyzed in this paper, and the reverse recovery loss is evaluated in a BOOST PFC converter using a silicon (Si) or silicon carbide (SiC) diode in the forward branch. Mathematical models of the forward conduction and reverse recovery losses are established to assess the influence of Si and SiC diodes. To characterize and quantify the losses related to diode reverse recovery, an 85~265V AC to 400V DC, 2kW BOOST PFC prototype is built with switching frequencies of 65kHz. It is found that the reverse-recovery inherent in a Si diode cannot be neglected. The switching loss is substantially smaller when the diode is a SiC one. In order to investigate further, a double pulse test rig is established, with the switch and the diode being either Si or SiC. The experimental results demonstrate that with a SiC diode, not only the diode conduction losses but also the transistor turn-on loss is greatly reduced.

Carbon nanodots (CNDs) are featured with a wide range of light absorption and excitation-dependent fluorescence. The emission enhancement of CNDs is of great interest for the development of nanophotonics. Although the phenomenon of plasmon-enhanced fluorescence for quantum dots and molecular dyes has been well investigated, rarely has it been reported for CNDs. In this work, a series of plasmonic nanoslit designs were fabricated and utilized for immobilization of CNDs in nanoslits and examination of the best match for plasmonic fluorescence enhancement of CNDs. In concert, to better understand the plasmonic effect on the enhancement, the surface optical field is measured with or without CND immobilization using a hyperspectral imaging system as a comparison, and a semianalytical model is conducted for a quantitative analysis of surface plasmon generation under the plane-wave illumination. Both the fluorescence and surface reflection light intensity enhancement are demonstrated as a function of nanoslit width and are maximized at the 100 nm nanoslit width. The analysis of surface plasmon–exciton coupling of CNDs in the nanoslit area suggests that the enhancement is primarily due to plasmonic light trapping for increased electromagnetic field and plasmon-induced resonance energy transfer. This study suggests that incorporating CNDs in the plasmonic nanoslits may provide a largely enhanced CND-based photoemission system for optical applications.