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This Letter presents a novel ultra-wide-band polarization-selective reflectarray with true-time delay. The reflectarray can be perceived as a combination of polarization grids and Vivaldi antennas, so is characterized by large bandwidth, low cross polarization, and polarization selectivity. A reflectarray of elements arranged in a 41 41 square grid operating from 6 to 32 GHz is designed, fabricated, and tested. The feed is provided by four pyramidal horn antennas operating at the working frequency (C, X, Ku/K, and Ka band). In measurements, the reflectarray shows stable radiation patterns from 6 to 32 GHz (more than 5:1 frequency range) and has a maximum aperture efficiency of 40%. It also has the low cross polarization below 28 dB across the entire band and has the characteristic of polarization selectivity.

Objective. The image reconstruction of ultrasound computed tomography is computationally expensive with conventional iterative methods. The fully learned direct deep learning reconstruction is promising to speed up image reconstruction significantly. However, for direct reconstruction from measurement data, due to the lack of real labeled data, the neural network is usually trained on a simulation dataset and shows poor performance on real data because of the simulation-to-real gap. Approach. To improve the simulation-to-real generalization of neural networks, a series of strategies are developed including a Fourier-transform-integrated neural network, measurement-domain data augmentation methods, and a self-supervised-learning-based patch-wise preprocessing neural network. Our strategies are evaluated on both the simulation dataset and real measurement datasets from two different prototype machines. Main results. The experimental results show that our deep learning methods help to improve the neural networks’ robustness against noise and the generalizability to real measurement data. Significance. Our methods prove that it is possible for neural networks to achieve superior performance to traditional iterative reconstruction algorithms in imaging quality and allow for real-time 2D-image reconstruction. This study helps pave the path for the application of deep learning methods to practical ultrasound tomography image reconstruction based on simulation datasets.

Despite decades of research, anticoagulation therapy recommendations in patients with left ventricular thrombus (LVT) are based on small, frequently outdated studies. There may not be strong enough evidence to support effective treatment.We postulated that using artificial intelligence clustering approaches, discrete patient groups may be identified that correspond to the effectiveness of anticoagulation in people with LVT.1,675 patients were retrospectively screened by the International Classification of Diseases 10th revision code in Fuwai Hospital, Beijing, from 2009 to 2021. All patients underwent transthoracic echocardiography. Only patients with a confirmed LVT were included after an imaging review by two independent experts. Principal components analysis and hierarchical clustering were applied to this study. The number of clusters and dimensions was determined objectively, with results validated using the bootstrapped approach. Major adverse cardiovascular and cerebrovascular events (MACCE) were the primary outcome, defined as the composite of cardiovascular death, ischemic stroke, and acute myocardial infarction. Cumulative incidence functions were generated for the competing risks of death during the follow-up period.1,068 patients with LVT were included, with median age of 55 years (IQR 44-64) and LVEF 38% (IQR 29-46). 890 (83.3%) patients were men. 4 Clusters were confirmed finally. Jaccard scores and heatmap confirmed the robustness and consistency of clustering. Compared with patients in cluster 2, those in cluster 1 were younger, with more females with worse cardiac (higher NT-proBNP level and lower ejection fraction) and renal (higher proportion of eGFR60 ml/min/1.73m2) function and higher risk of embolism (higher D-Dimer level and higher proportion of round LVT). Compared with cluster 2, cluster 1 had a higher risk of all-cause death, cardiovascular death, and MACCE (all P.001). No significant changes in the composition of the 2 clusters have occurred over time (all P for trend.05). Across the whole cohort of patients in LVT, anticoagulation did not significantly reduce MACCE compared with participants without anticoagulation, with an HR of 1.29 (95% CI 0·97-1.71, P=.08). There was a statistically significant reduction in MACCE with anticoagulation in cluster 1, with an HR of 0.67 (95% CI 0.46-0.98, P=.04). However, in cluster 2, anticoagulation can increase the incidence of MACCE with an HR of 1.59 (95% CI 1.03-2.46, P=.04) and significant interaction (P=.03).A clustering method based on artificial intelligence in patients with LVT may tell prognostic responses from anticoagulation. Our study confirms that not all patients with LVT benefit from anticoagulation, but only those at high risk. This included a cluster of patients with suboptimal efficacy and another group where anticoagulation reduced MACCE.

Objective To summarise the dynamic characteristics of COVID-19 transmissibility; To analyse and quantify the effect of control measures on controlling the transmissibility of COVID-19; To predict and compare the effectiveness of different control measures. Methods We used the basic reproduction number ($${R}_{0}$$ R 0 ) to measure the transmissibility of COVID-19, the transmissibility of COVID-19 and control measures of 176 countries and regions from January 1, 2020 to May 14, 2022 were included in the study. The dynamic characteristics of COVID-19 transmissibility were summarised through descriptive research and a Dynamic Bayesian Network (DBN) model was constructed to quantify the effect of control measures on controlling the transmissibility of COVID-19. Results The results show that the spatial transmissibility of COVID-19 is high in Asia, Europe and Africa, the temporal transmissibility of COVID-19 increases with the epidemic of Beta and Omicron strains. Dynamic Bayesian Network (DBN) model shows that the transmissibility of COVID-19 is negatively correlated with control measures. Restricting population mobility has the strongest effect, nucleic acid testing (NAT) has a strong effect, and vaccination has the weakest effect. Conclusion Strict control measures are essential for controlling the COVID-19 outbreak; Restricting population mobility and nucleic acid testing (NAT) have significant impacts on controlling the COVID-19 transmissibility, while vaccination has no significant impact. In light of these findings, future control measures may include the widespread use of new NAT technology and the promotion of booster immunization.

Sandstone properties can be greatly influenced by water, and many scholars have investigated the interaction between sandstone and water, but paid less attention to the assessment of crack development, fragment features, and damage evolution, which are important factors for evaluation of hydraulic fracturing effect. In this study, uniaxial compression tests were conducted on sandstone specimens in dried, natural, and saturated state, respectively. The generated fragments were collected, and acoustic emission signals were recorded continuously. The grain size distribution and shape description as well as fractal dimension of fragments were all analyzed. Moreover, AE parameter evolution of RA (the ratio of rise time to amplitude) versus AF (average frequency) was obtained and AE damage analysis was carried out. Compared to saturated specimens, dried and natural specimens generated a larger amount of fragments in medium, fine, and micro-grain groups with relatively larger fractal dimension. The average release of cumulative AE energy of dried and natural specimens is much greater than those of saturated specimens. The distributions of RA versus AF imply that water saturation increases tensile fracture whereas decreases shear fracture, which are consistent with the macroscopic failure modes. Compared to saturated and natural specimens, dried specimens which generate more macro-flaws have relatively lower damage correction factor $$\eta$$ and higher damage variable D0. The obtained results can be used as the scientific bases to study sandstone weakening mechanism under water influence.

Oropharyngeal candidiasis (OPC) is an opportunistic infection treated with anti-fungal agents. Herein, we evaluate the efficacy and safety of miconazole buccal tablets (MBT) and itraconazole capsules in the localized treatment of patients with OPC. In this multi-centered, double-blinded, phase III trial (CTR20130414), both males and non-pregnant females (≥18 years) with OPC were randomized (1:1) to MBT plus placebo (experimental group) or itraconazole capsules plus placebo (control group). The primary endpoint was clinical cure at the end-of-treatment period [visit 4 (V4)] while secondary endpoints were clinical remission rates, partial remission rates, mycological cure, clinical relapse, and adverse events (AEs). All endpoints were statistically analyzed in both the full analysis set (FAS) and per-protocol (PP) set. A total of 431 (experimental: 216; control: 215) subjects were included. At V4, in the FAS set, the clinical cure was achieved in 68% and 59% patients in experimental and control groups, respectively with a treatment difference of 9% [95% confidence interval (CI): -1,19; P.001] demonstrating non-inferiority of MBT over itraconazole. At V4, mycological cure rates were 68.2% and 42.0% in the experimental group and control groups (P.001), respectively in FAS. The relapse rates were 5.4% and 6.6%, respectively, in the experimental and control groups. A total of 210 patients experienced AEs during treatment with 47.7% in the experimental group and 49.8% in the control group with no deaths. This study demonstrated that once-daily treatment with MBT was non-inferior to itraconazole with higher mycological cure rates and was tolerable with mild AE in patients with OPC.Miconazole is an antifungal drug against certain types of fungus or yeast infections. In this study, we showed that treatment with once-daily miconazole buccal tablets was as effective as systemic itraconazole capsules in Chinese patients infected by oropharyngeal candidiasis with minimum side effects.

Organic science & technology (OST) become the frontier horizon after nanotechnology, information technology as well as biotechnology toward the era of consciousness. Organic nanogridarenes (ONGAs) are becoming robust nanoscaffolds for next-generation multifunctional/intelligent semiconductors with tunable cross-scale features. However, the prerequisite of trans-dimensional & intelligent design is to clarify the gridization rules for the discovery of the powerful molecular gridization protocols. Here, we report an efficient and multiselective Csp2-Csp3 gridization based on dual halogen bonding (X···π and X···S, X = Br, I) self-activated electrophilic substitution of halogenated electron-rich molecular blocks under supersonic conditions. Windmill-type nanogrids of cyclopenta[1,2-b:5,4-b']dithiophene (WG4) were obtained with the maximum path selectivity (96%), nanogrid-size selectivity (67%), site-selectivity (>99%) and moderate diastereoselectivity (WG4-1-6:WG4-2-6:WG4-3-6:WG4-4-6 =1:3.3:5.3:0), superior to the previous Friedel-Crafts gridization. Mechanistic studies have revealed the roles of XBs where the X···S bonding accelerates dehalogenation after electrophilic attack, and the X···π bonding leads to the multiselectivity of WG4. Impressively, C2-symmetric WG4-1-6 (21×21×15 Å) crystallizes into a Fd3̄c space group as the 16th pure organic molecules in CCDC library and hierarchically self-assemble into a complex 3D porous superstructure.

Low-frequency narrow-band noise is one of the important components in the slat noise. Based on the transient flow field analysis for multi-element airfoil 30P-30N, the main mode characteristics of the slat pressure fluctuation are analyzed by means of proper orthogonal decomposition (POD) and dynamic model decomposition (DMD), and the key feature modes and the distribution of narrow-band frequencies for the slat are obtained. Empirical mode decomposition (EMD) and cross-correlation analysis are used to reconstruct the signal by preserving the low frequency characteristics of the original transient pressure signal. The locations of noise sources of the low-frequency narrow-band are determined according to the delay time and geometric relationship for characteristic points. The results show that the low-frequency narrow-band sound sources are mainly concentrated on regions of feature modes with large pressure fluctuations, such as slat trailing edge, downstream of the shear layer and the recirculation zone. Meanwhile, there are still some sound sources of low-frequency narrow-band distributed in regions of non-featured modes. The key characteristics of these regions are the interaction of flow structure between the trailing edge of the slat and the leading edge of the main wing due to collision of the shear layer.

In recent years, real-time microscopic imaging of laser-induced periodic surface structure (LIPSS) formation during laser micromachining was found to be favorable for investigating the physical origin of the LIPSS on various materials. In this paper, an ultraviolet-oblique-illumination high-resolution microscopic imaging setup, combined with a focal spot enlarging technique, was used for observing the initiation, development, and maturation of the LIPSS. The research focuses on the influence of random surface deposits, laser-etched microtrench, and pre-existing ripples on laser-induced LIPSS under pulse-by-pulse irradiation. Compared to the flat region on the SiC surface, both random surface deposits and the microtrench promote the phase-locking growth of the LIPSS, but in different ways. The finite-difference time-domain method shows that random surface deposits may promote the LIPSS growth through the action of the interference field of incident light with its scattered light on deposits. A microtrench covered with high-spatial-frequency LIPSS may assist LIPSS growth by absorption enhancement-induced easier transferring of the incident periodic field. Finally, phase-locking growth of the LIPSS was found to be the result of the light-trapping effect of high-refractive-index sidewalls of the LIPSS valley. Our results showed that local morphologies were very important in LIPSS formation.

The normal operation of aircraft and flights can be affected by various unpredictable factors, such as severe weather, airport closure, and corrective maintenance, leading to disruption of the planned schedule. When a disruption occurs, the airline operation control center performs various operations to reassign resources (e.g., flights, aircraft, and crews) and redistribute passengers to restore the schedule while minimizing costs. We introduce different sources of disruption and corresponding operations. Then, basic models and recently proposed extensions for aircraft recovery, crew recovery, and integrated recovery are reviewed, with the aim of providing models and methods for different disruption scenarios in the practical implementation of airlines. In addition, we provide suggestions for future research directions in these topics.

OBJECTIVES We aimed to explore the impact of 7-Fr sheaths on the incidence of early radial artery occlusion (RAO) after transradial coronary intervention (TRI) in Chinese patients. BACKGROUND RAO precludes future use of the vessel for vascular access. Transradial catheterization is usually performed via 5-Fr or 6-Fr catheters; 7-Fr sheath insertion enables complex coronary interventions but may increase the RAO risk. METHODS We prospectively enrolled 130 consecutive patients undergoing complex TRI using 7-Fr sheaths. Radial artery ultrasound assessment was performed before and after TRI. Early RAO was defined as the absence of flow on ultrasound within 6-24 hr after TRI. Multivariate logistic regression was used to determine the factors related to early RAO after TRI. RESULTS 7-Fr sheaths were mainly used for chronic total occlusion (44.6%), bifurcation (30.0%), and tortuous calcification (25.4%) lesions. All patients were successfully sheathed. Percutaneous coronary intervention (PCI) procedural success was 96.2%; 119 patients (91.5%) had preserved radial artery patency after TRI. All 11 RAO cases (8.5%) were asymptomatic. The radial artery diameter was significantly larger postoperatively (3.1 ± 0.4 mm) than preoperatively (2.6 ± 0.5 mm) (p

To assess the predictive value of stress hyperglycemia ratio (SHR) for long-term mortality after acute myocardial infarction (AMI) in patients with and without diabetes.We evaluated 6892 patients with AMI from the prospective, nationwide, multicentre China Acute Myocardial Infarction registry, of which 2820 had diabetes, and the remaining 4072 were nondiabetic patients. Patients were divided into high SHR and low SHR groups according to the optimal cutoff values of SHR to predict long-term mortality for diabetic and nondiabetic patients, respectively. The primary endpoint was all-cause mortality at 2 years.The optimal cutoff values of SHR for predicting 2-year mortality were 1.20 and 1.08 for the diabetic and nondiabetic population, respectively. Overall, patients with high SHR were significantly associated with higher all-cause mortality compared with those with low SHR, in both diabetic patients (18.5% vs. 9.7%; hazard ratio [HR] 2.01, 95% confidence interval 1.63-2.49) and nondiabetic patients (12.0% vs. 6.4%; HR 1.95, 95%CI 1.57-2.41). After the potential confounders were adjusted, high SHR was significantly associated with higher risks of long-term mortality in both diabetic (adjusted HR 1.73, 95%CI 1.39-2.15) and nondiabetic (adjusted HR 1.63, 95%CI 1.30-2.03) patients. Moreover, adding SHR to the original model led to a slight albeit significant improvement in C-statistic, net reclassification, and integrated discrimination regardless of diabetic status.This study demonstrated a strong positive association between SHR and long-term mortality in patients with AMI with and without diabetes, suggesting that SHR should be considered a useful marker for risk stratification in these patients.ClinicalTrials.gov NCT01874691.

This article presents an advanced method for monolithic 3-D integrated circuits (ICs)’ test compression based on 3-D Haar wavelet transforms. The main purpose of this study is to reduce the test response data consumption while achieving higher fault coverage using new Haar wavelet transforms. Considering the faultiness of test compression, this article would like to introduce the “3-D Haar wavelet transforms,” which would update part of 2-D butterfly unit into 3-D butterfly unit based on the traditional Haar wavelet transforms to simplify the test response output nodes. To better achieve the purpose, a new no-X-unknown-carry adder is applied to build 3-D no-X-unknown-carry Haar wavelet transform (3-D_NxUC_HWT), which not only could solve X-masking but also could transmit an X-bit efficiently to make a delay fault diagnosis. In addition, the constructed reuse architecture makes it possible to plan reasonably the test compression structure by making full use of monolithic interlayer vias to shorten the parallel transmission length. In this study, the test point data are output to the test compressor in parallel through interlayer vias and the compressed results are shifted out by serial scan chain to shorten the test time. The experimental results clearly demonstrate that this method has superiority of higher test coverage, faster test time, fewer test analysis data, and smaller hardware overhead.

Molecular separations that enable selective transport of target molecules from gas and liquid molecular mixtures, such as CO2 capture, olefin/paraffin separations, and organic solvent nanofiltration, represent the most energy sensitive and significant demands. Membranes are favored for molecular separations owing to the advantages of energy efficiency, simplicity, scalability, and small environmental footprint. A number of emerging microporous organic materials have displayed great potential as building blocks of molecular separation membranes, which not only integrate the rigid, engineered pore structures and desirable stability of inorganic molecular sieve membranes, but also exhibit a high degree of freedom to create chemically rich combinations/sequences. To gain a deep insight into the intrinsic connections and characteristics of these microporous organic material-based membranes, in this review, for the first time, we propose the concept of organic molecular sieve membranes (OMSMs) with a focus on the precise construction of membrane structures and efficient intensification of membrane processes. The platform chemistries, designing principles, and assembly methods for the precise construction of OMSMs are elaborated. Conventional mass transport mechanisms are analyzed based on the interactions between OMSMs and penetrate(s). Particularly, the 'STEM' guidelines of OMSMs are highlighted to guide the precise construction of OMSM structures and efficient intensification of OMSM processes. Emerging mass transport mechanisms are elucidated inspired by the phenomena and principles of the mass transport processes in the biological realm. The representative applications of OMSMs in gas and liquid molecular mixture separations are highlighted. The major challenges and brief perspectives for the fundamental science and practical applications of OMSMs are tentatively identified.

The direct C–H amidation or imidation of metallaaromatics with N-bromoamides or imides has been achieved under mild conditions and leads to the formation of a family of N-functionalized metallapentalyne derivatives. A unique 1,5-bromoamidated species has been identified, and can be viewed as a σH-adduct intermediate in a nucleophilic aromatic substitution. The 1,5-addition of both electrophilic and nucleophilic moieties into the metallaaromatic framework demonstrates a novel pathway in contrast to the typical radical process of arene C–H amidation involving N-haloamide reagents.

With the vigorous development of deep learning and the widespread use of mobile robots, automatic driving has gradually become a research hotspot. Environment perception is the most important part of automatic driving technology, and the purpose of environment perception is to distinguish the environmental content. Therefore, accurate and efficient image semantic segmentation method is becoming more and more important. In this paper, we introduce a deep semantic segmentation solution: IIE-SegNet: Deep semantic segmentation network with enhanced boundary based on image information entropy. At present, deep learning based on semantic segmentation solutions has some problems, such as low segmentation accuracy for small-scale objects and unclear boundary of segmented objects. Our method preserves the boundary of the segmentation object, and has higher segmentation accuracy for small-scale objects. In our method, the features of the underlying pooling layer are added to the ASPP structure of the encoding module, and the image information entropy of the previous pooling layers is introduced into the decoding module. We also introduce focal loss to solve the problem of imbalance between positive and negative samples. Finally, the test results on the extended Pascal VOC 2012 test set, abbreviated to Exp-Pascal VOC 2012 test set show that the proposed method has better performance on Exp-Pascal VOC 2012 test set compared with the advanced methods at the present stage, the segmentation accuracy of small-scale targets is higher, and the boundary is clearer.

A novel serrated ground plane (NSGP) for na low-loss reflectarray antenna is presented in this paper. Compared with a conventional smooth ground plane (CGP), the NSGP consists of a series of serrated elements, which can reflect the incident waves in the main beam direction, so the losses of the reflectarray can be effectively reduced. The principle and losses of reflectarray antennas are studied and analyzed. Then, a low-loss NSGP is proposed, and two design methods for the NSGP are given in this paper. Finally, a reflectarray antenna with elements arranged in a 15×15 grid is designed, simulated and measured with the NSGP and CGP respectively within the frequency from 12.88 to 13.88GHz. The results show that the reflectarray antenna with the NSGP can effectively utilize the reflected waves and has a maximum higher gain of 0.681 dB compared with the gain of the reflectarray with the CGP. This NSGP has a potential to be used in the high accurate design of the reflectarray which requires to realize beam forming, low-loss, high-efficiency, etc.

Microporous polymer membranes hold great promise in carbon capture. However, engineering a continuous CO2-selective microporous network to achieve ultrahigh gas permeance and desirable selectivity remains a grand challenge. Aiming to manipulate the pore architecture and pore chemistry to implement efficient separation, knitted microporous polymer membranes are fabricated by in situ knitting composite membranes comprised of polyphenylene oxide (PPO) polymer and benzyl alcohol (BnOH). Specifically, the crosslinkers, formaldehyde dimethylacetal, bridge the neighboring aromatic backbones of PPO chains and BnOH to construct a highly crosslinked network with microporosity. By increasing the structural bridge density, the BET surface area of membranes increases from 4 to 538 m2 g−1. The formation of a highly interconnected microporous network provides remarkably increased permeability. Meanwhile, BnOH as a hydroxyl-containing functional building unit is knitted into micropore skeletons, which can directly tune the pore size and improve the CO2-philicity for enhanced selectivity. The resulting membrane displays an ultrahigh permeability of 4651.2 barrer with a CO2/CH4 selectivity of 27, and demonstrated good resistance to plasticization (up to 30 bar) and aging (for 190 days). This knitting strategy enabling versatile combination of building units with different structures and special functionalities may set up an innovative platform for fabricating a broad range of advanced membranes.

Target state estimation is a key technology for unmanned underwater vehicles (UUVs) to achieve target tracking, collision avoiding, formation control, and other tasks. Compared with other measurement methods, underwater measurement has lower reliability due to the uncertainty of sonar detection. In this case, the performance of target state estimation depends heavily on the target motion model. However, the dynamics of UUVs are very complex and nonlinear. Although many state estimation methods for nonlinear systems have been proposed, the complex dynamics of UUV and uncertainty in sonar detection remain challenges for underwater target state estimation problems. This article proposes a gated recurrent unit (GRU)-based particle filter (PF) to improve the performance of the target state estimator for UUVs. A deep neural network framework based on GRUs is used to establish the mapping between the previous measurements and the current target states. This neural network learns the dynamics model of UUVs and recognizes the measurement noise. The proposed filter samples from previous measurements of the target UUV, and the fully trained deep neural network predicts the current states of the sampled particles. The proposed method solves the low accuracy and instability caused by motion modeling errors and system nonlinearity. The simulation results show that the proposed GRU-based PF for UUV state estimation has better accuracy and stability than the traditional state estimation methods. All the simulations are done with the noise which is Gaussian noise that can pass through a nonlinear transformation.

Visual odometry (VO) is one of the essential techniques in mobile robots field; an accurate VO system is of great significance for mobile robot simultaneous localization and mapping. As for traditional monocular VO systems, they work by presuming the monocular scale is 1 (scale = 1), or relying on ground truth (GT) to estimate scale. As a result, the traditional monocular VO systems estimate the pose state with big drift or cannot work on the image sequence without GT. Although some classical monocular VO systems have been proposed, they still have imperfect performance or even unable to work in some extreme scene conditions, such as scene is monotony without obvious texture information or camera large-scale displacement motion. As for learning-based VO system, it is realized by training deep neural networks in supervised or self-supervised manner to end-to-end estimate the pose state; however, the accuracy of pose estimation entirely depends on the ability of networks. Although the ability of networks can be improved by increasing the number of training data sets and optimizing the network structure, it is inevitable to encounter problems such as insufficient generalization ability and insufficient accuracy on rotational pose estimation. In this article, a monocular VO system named DL_Hybrid is proposed, which takes full advantage of DL networks used in image processing and geometric localization theory based on hybrid pose estimation methods. The DL_Hybrid VO system can estimate a six-DoF pose one-frame-by-one-frame and recover camera trajectory, and it can extract accurate key points from per-frame even in extreme scene condition, and it has good performance even in the extreme moving condition, such as camera rotation-only action or static action, also it can work well in the condition of camera large-scale displacement motion. The real scale is also accurately estimated without depending on GT, and the pose estimation method is designed based on hybrid 2d–2d and 3d–2d localization theory to make the DL_Hyrid VO system to estimate translational and rotational information with accuracy and robustness. Experimental results show that the proposed DL_Hybrid VO system has a better performance than traditional and learning-based VO systems.

Highly efficient and stable blue organic lighting-emitting diodes (OLEDs) continue to be a challenge. The substitution strategy has been proven to be one of the most effective chemical approaches to improve the electroluminescence (EL) performance and the operational stability of blue OLEDs based on thermally activated delay fluorescent (TADF) emitters. Herein, the effects of tert-butyl and 9-phenyl-9-fluorenyl substituents on the physicochemical properties and EL performance are systematically studied for aromatic-imide-based TADF molecules. The robust 9-phenyl-9-fluorenyl units outperform the tert-butyl groups in improving the thermal and electrochemical stability. Consequently, sky blue OLEDs based on 4-DPFCzAIAd containing 9-phenyl-9-fluorenyl substituents exhibit excellent comprehensive EL performance with a maximum external quantum efficiency of 28.2% and a long LT50 (time to 50% of initial luminance) of 178 h at an initial luminance of 500 cd m−2, which is much better than that of the device with a tert-butyl substituted emitter. These results demonstrate that the 9-phenyl-9-fluorenyl substituent is superior to the tert-butyl group in constructing TADF emitters for efficient and stable blue OLEDs.

The extent and quality, i.e. consistency, of the fusion bonding between filaments that occurs during the fused filament fabrication (FFF) process play an important role in determining the mechanical performance of 3D printed polymeric parts. This present research is designed to quantify these parameters of the fusion bonding between individual filaments deposited during the 3D printing process. Polyamide 6 (PA6) specimens were prepared from both 3D printed single-layer and single-filament films. Also, to provide a benchmark material, 3D printed PA6 films prepared by the FFF process were further processed by using compression moulding (CM) to investigate whether the fusion bonding could be enhanced. An essential work of fracture method was employed to evaluate the fusion bonding between the filaments by determining the value of the specific essential work of fracture, we, and the associated experimental reproducibility. The higher value of we, and the relatively low degree of scatter determined for the benchmark material revealed that the extent and quality of fusion bonding attained when using only the FFF process clearly needed to be improved when parts are fabricated for practical applications. To study the effect of temperature on the fusion bonding, the structural detail and fracture surfaces of thin polymer films were studied, with the thermal history of the deposited filaments also being measured using a thermal camera.

Continuous electroencephalogram (EEG) recording is vital for brain science research, monitoring pathological and physiological conditions, and the diagnosis of brain disease. Conventional wet electrodes require skin preparation and a gel electrolyte to reduce electrode–skin interface impedance (EII), which limits its further application in long-term EEG signal recording. Microneedle-array electrodes (MAEs) have been employed in EEG recording, as they can be used directly without skin preparation or the gel electrolyte. However, most microneedles used in MAE are rigid and have a high aspect ratio; thus, they can break easily. Hence, we developed a novel bendable MAE for EEG recording. It is made of a flexible polydimethylsiloxane (PDMS) pillar array with rigid microneedle tips. The PDMS pillar array could help the MAE pass through hair and enable the microneedle tips to penetrate a stratum corneum layer into a scalp, thus reducing the EII. Moreover, the PDMS pillar array is bendable, which prevents the microneedles tips from breaking. The MAE can record EEG signals well in a BIOPAC system and an Emotiv EPOC+ device. The bendable MAE may be an alternative electrode for long-term EEG recording.

Mode-locked fibre lasers (MLFLs) are fundamental building blocks of many photonic systems used in industrial, scientific and biomedical applications. To date, 1–2 μm MLFLs have been well developed; however, passively mode-locked fibre lasers in the visible region (380–760 nm) have never been reported. Here, we address this challenge by demonstrating an all-fibre visible-wavelength passively mode-locked picosecond laser at 635 nm. The 635 nm mode-locked laser with an all-fibre figure-eight cavity uses a Pr/Yb codoped ZBLAN fibre as the visible gain medium and a nonlinear amplifying loop mirror as the mode-locking element. First, we theoretically predict and analyse the formation and evolution of 635 nm mode-locked pulses in the dissipative soliton resonance (DSR) regime by solving the Ginzburg-Landau equation. Then, we experimentally demonstrate the stable generation of 635 nm DSR mode-locked pulses with a pulse duration as short as ~96 ps, a radio-frequency signal-to-noise ratio of 67 dB and a narrow spectral bandwidth of 1 nm) and modulated optical spectrum. This work represents an important step towards miniaturized ultrafast fibre lasers in the visible spectral region., Photonics: Lighting the way ultrafast compact visible light lasers Chinese scientists have demonstrated a low-cost and compact ultrafast passively mode-locked laser that operates in the visible light spectrum and could see use in a range of industrial, scientific, and biomedical applications. Although Mode-locked fibre lasers (MLFLs) are the fundamental building blocks of many photonic systems, ultrafast lasers in the visible light spectral region are costly and challenging to make. For the first time, Zhengqian Luo and colleagues from Xiamen University in China have demonstrated a visible-wavelength passively mode-locked all-fibre laser that operates in the dissipative soliton resonance regime. The laser generates picosecond pulses of light at 635 nanometres and represents an essential step towards miniaturized ultrafast fibre lasers in the visible light range. The work lays the foundations for photonic devices for use in applications such as material processing, medicine, spectroscopy, and optical communications.