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AIMS The aim of this study was to evaluate alterations in left ventricular (LV) systolic and diastolic function in subjects with prediabetes and diabetes using cardiovascular magnetic resonance-feature tracking (CMR- FT). METHODS We included 35 subjects with prediabetes, 30 subjects with diabetes, and 33 healthy controls of similar age and sex distributions who underwent CMR examination. LV global radial, circumferential, and longitudinal strain (GRS, GCS, and GLS), peak systolic strain rate (PSSR), and peak diastolic strain rate (PDSR) were measured and compared among the three groups. Pearson's correlation and linear regression analyses were applied for statistical analyses. RESULTS Subjects with prediabetes and diabetes had a significantly lower GLS than healthy controls, but there were no significant differences in ejection fraction (EF), GRS, GCS, or global radial, circumferential and longitudinal PSSR among the three groups. Global radial, circumferential, and longitudinal PDSR in patients with diabetes were all significantly lower than those in the healthy controls. Compared to subjects with prediabetes, patients with diabetes had a significantly lower global circumferential PDSR. Global longitudinal PDSR in subjects with prediabetes was significantly lower than that in healthy controls. Multivariable linear regression analyses demonstrated that elevated HbA1c levels were independently associated with decreased global circumferential and longitudinal PDSR (β = -0.203, p = 0.023; β = -0.207, p = 0.040, respectively). CONCLUSIONS CMR-FT has potential value to evaluate early alterations in LV systolic and diastolic function in subjects with prediabetes and diabetes. Elevated HbA1c levels were independently associated with impaired LV diastolic function in the general population free of overt cardiovascular diseases.

The development of biologically active multifunctional hydrogel wound dressings can assist effectively to wound regeneration and also has influenced multiple functions on wound injury. Herein, we designed a carbon-based composited injectable silk fibroin hydrogel as multifunctional wound dressing to provide effective anti-bacterial, cell compatibility and in vivo wound closure actions. Importantly, the fabricated injectable hydrogel exhibit sustained drug delivery properties, anti-oxidant and self-healing abilities, which confirm that composition of hydrogel is highly beneficial to tissue adhesions and burn wound regeneration ability. Frequently, designed injectable hydrogel can be injected into deep and irregular burn wound sites and would provide rapid self-healing and protection from infection environment with thoroughly filled wound area. Meanwhile, incorporated carbon nanofillers improve injectable hydrogel strength and also offer high fluid uptake to hydrogel when applied on the wound sites. In vitro MTT cytotoxicity assay on human fibroblast cell lines establish outstanding cytocompatibility of the injectable hydrogel and also have capability to support cell growth and proliferations. In vivo burn wound animal model results demonstrate that the hydrogel dressings predominantly influenced enhanced wound contraction and also promoted greater collagen deposition, granulation tissue thickness and vascularization. This investigation's outcome could open a new pathway to fabricate multifunctional biopolymeric hydrogel for quicker burn wound therapy and effectively prevents microenvironment bacterial infections.

The intrinsically poor optical absorption and short carrier lifetime of graphene have restricted its practical application in photodetectors. Carbon nanodots (CNDs) have received much attention due to their fascinating optical properties, environmentally friendly nature, small size, and superiority of a large optical absorptivity. Thus, in this article, a hybrid photodetector based on CNDs and graphene has been proposed for the solar-blind ultraviolet (UV) photodetection, in which CNDs were integrated with graphene to form a hybrid structure which was capable of detecting UV light with 254 nm. Here, this article also demonstrated that a high photoresponsivity of ~433.33 A/W and a detectivity of $\sim 1.08\times 10^{{12}}$ Jones can be obtained in the hybrid photodetector. UV illumination causes photogenerated electrons and holes in CNDs. Holes transfer to graphene and then recirculate many times, which originates from the high carrier mobility of graphene and the prolonged lifetime of excited electrons that remain trapped in CNDs. Our result demonstrates that the integration of graphene and CNDs shows better optical absorption and wavelength selectivity. Together with the mechanism, it paves a step for practical applications of quantum dots sensitized graphene-based photodetectors.

This paper focuses on consensus reaching process (CRP) under social network in which the trust relationship expressed by linguistic information. A new feedback mechanism in social network group decision making (SN-GDM) is proposed, which mainly consists of the following two aspects: (1) The propagation of distributed linguistic trust is investigated to study trust relation among experts; (2) A maximum self-esteem degree based feedback mechanism is developed to produce personalized advice for reaching higher group consensus. To do so, a novel linguistic trust propagation method is proposed to obtain the complete trust relationship among group. The self-esteem degree is used to define the extent that an individual makes concessions. Then, a maximum self-esteem degree based optimal feedback mechanism is built to produce personalized advice to help inconsistent experts make change of their opinion. Its novelty lies in the establishment of an optimization model with the nonlinear group self-esteem degree function as the objective function while group consensus threshold as the restrictions. Therefore, the inconsistent experts will reach a group consensus with the minimum loss of self-esteem degree, and then, it achieves the optimal balance between individual self-esteem and group consensus. Finally, a ranking process is applied to derive the appropriate consensus solution.

Mg alloys are promising structural materials in aerospace industry due to high strength to weight ratio. However, most Mg alloys are limited in aircraft cabins due to their susceptibility to ignition and burning. To improve fire resistance, adding alloying elements is a strategy. Thus, the goal of this study is to explore the effects of alloying elements Al, Zn, and rare earths on Mg-alloy flammability by experiment, using the system and procedures in compliance with the Federal Aviation Administration (FAA) standards for Mg-alloy flammability test. Six commercial Mg alloys with different alloying elements (AZ91E, ZK61A, ZE63A, EZ33A, WE43B, and EV31A) were tested. Results indicate that Mg alloys with Al or Zn elements were of short ignition time and high weight loss. With rare earths, Mg-alloy flammability was suppressed obviously. It appears that this suppression effect with rare earth addition was attributed to the formation of protective oxide film on the surface of molten alloy. Further, a heat transfer model was established to analyze the temperature evolution of the test specimen subjected to the sonic burner–generated flame by FAA standards, and ignition temperatures of all testing Mg alloys were predicted based on the experimental ignition time. The predicted results confirm that with rare earths addition, ignition was delayed after melting by the protective oxide film formed on the surface of the molten alloy.

The aim of this study was to explore the pivotal genes or lncRNAs involved in the progression of atrial fibrillation (AF) -valvular heart disease (VHD). The mRNA profiling GSE113013 was obtained from the Gene Expression Omnibus database. The identification of differentially expressed genes (DEGs) and differentially expressed long non-coding RNAs (DElncRNAs) was performed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were carried out for DEGs. Then, the construction of the protein-protein interaction (PPI) network was conducted. An lncRNA-miRNA-target ceRNA network was constructed after obtaining microRNAs (miRNA) related to DElncRNAs. Ultimately, key disease-related genes were screened. A total of 399 DEGs and 145 DElncRNAs were obtained. There were 283 nodes and 588 interaction pairs in the PPI network, and synaptosome-associated protein 25 (SNAP25) had higher degrees (degree = 22) in the PPI network. There were 65 interaction pairs in the ceRNA network. Here, Baculoviral IAP Repeat Containing 5 (BIRC5) was regulated by hsa-miR-1285-3p, which was regulated by lncRNA NPHP3-AS1. Gap Junction Protein Alpha 5 (GAJ5) was regulated by hsa-miR-4505, hsa-miR-1972, and hsa-miR-1199-5p. In particular, GAJ5 was enriched in the function of ion transmembrane transport regulation, whereas BIRC5 was enriched in the function of apoptosis-multiple species pathway. Similarly, Potassium Inwardly Rectifying Channel Subfamily J Member 6 (KCNJ6) was enriched in the function of an ion channel complex. VENN analysis identified BIRC5 and GJA5 as key AF-related genes. KCNJ6, SNAP25, GJA5, BIRC5, hsa-miR-1285-3p, and lncRNA NPHP3-AS1 were likely to be associated with AF-VHD development.

CsPbBr3-based photodetectors (PDs) have aroused enormous attention owing to their low-cost solution processing, outstanding optoelectronic properties, and remarkable stability. However, their performance remains a big challenge to meet the requirements for practical applications due to severe carrier recombination caused by the inferior film quality. Herein, we demonstrated that the introduction of congeneric CsPbBr3 quantum dots (QDs) to decorate the surface of CsPbBr3 films can effectively improve the surface morphology and reduce the surface defects. After detailed characterizations, we can infer that the functions of the QDs are to fill the pinholes, cracks, and grain boundaries and passivate the uncoordinated Pb and Br ions. Subsequently, PDs with a device architecture of indium tin oxide (ITO)/ZnO/CsPbBr3 film/CsPbBr3 QDs/Au electrode are fabricated, exhibiting a high responsivity of 0.88 A W−1, a superior specific detectivity of 2.15 × 1012 Jones, a large linear dynamic range of 119 dB, and a fast rise (fall) time of 8.1 μs (27.2 μs) at zero bias. The value of the maximum detectivity can reach 7.53 × 1012 Jones when operated at a bias of 0.04 V. Besides, a negligible change of performance is observed after 1000 hours of storage under 60% relative humidity conditions, which verifies the excellent stability of our PDs. Superior performance and stability suggest that our surface passivation method with congeneric QDs is feasible and can pave the way for future commercial applications of perovskite PDs.

Perovskite single crystals (PSCs) can be used to fabricate high performance photoelectric detectors due to their superior optoelectronic characteristics. Generally, an external electric field needs to be applied in PSC-based detectors to improve their charge collection efficiency. However, the large external electric field increases the dark current, which will enlarge the noise current. To alleviate this drawback, an approach of fabricating a PSC-based heterojunction is proposed in this work, which contributes to reduced dark current in a relatively high reverse electric field. In this study, a heterojunction formed by epitaxially growing MAPbBr3 PSCs on Bi3+-doped MAPbCl3 PSCs is reported, and it shows relatively low trap density and higher built-in potential. The as-fabricated Au-MAPbBr3/Bi3+-doped MAPbCl3 PSC heterojunction-Au photodiode shows smaller dark current density, better long-term current stability and reduced noise level by approximately four orders compared to the Au–MAPbBr3 PSCs–Au photoconductor device under an external reverse voltage of 100 V (mean electric field of ∼31.5 V mm−1). Moreover, the pN heterojunction photodiode shows favorable X-ray detection performance, with a fast response time of 4.89 μs and high sensitivity of 1.72 × 103 μC Gyair−1 cm−2 for 50 kVp X-ray photons under a reverse electric field of 31.5 V mm−1. This work confirms that the epitaxial fabrication of PSC heterojunctions may be a promising strategy to enhance the performance of X-ray photodetectors.

Network simulation is a fundamental service for performance testing and protocol design in wireless networks. Due to the wireless dynamics, it is highly challenging to provide repeatable and reliable simulation results that are comparable to the empirical experimental results. To achieve repeatability for simulation, the existing works focus on reproducing the behaviors on individual links. However, as observed in recent works, individual link behaviors alone are far from enough to characterize the protocol-level performance. As a result, even if the link behaviors can be simulated very closely, these works often fail to simulate the protocol performance with high reliability. In this article, we propose a novel performance-aware simulation approach which can preserve not only the link-level behaviors but also the performance-level behaviors. We first combine the spatial-temporal link diversity to devise an accurate performance model. Based on the model, we then propose a Performance Aware Hidden Markov Model (PA-HMM), where the protocol performance is directly fed into the Markov state transitions. Compared to the existing works, PA-HMM is able to simulate both link-level behaviors and high-level protocol performance. We conduct extensive testbed and simulation experiments with broadcast and anycast protocols. The results show that 1) the proposed model is able to accurately characterize communication performance for both broadcast and anycast and 2) the protocol performance is closely simulated as compared to the empirical results and the PA-HMM based simulation is more repeatable compared to the existing works.

Resumo Fundamento: A taxa de falha de enxerto de veia safena um ano após a cirurgia de revascularização do miocárdio varia de 10% a 25%. O objetivo deste estudo foi de investigar se a atorvastatina pode reduzir o acúmulo de células musculares lisas vasculares para inibir a hiperplasia intimal por meio da inibição da via p38 MAPK. Métodos: Quarenta e cinco ratos Sprague-Dawley foram randomizados em três grupos. Trinta ratos foram submetidos à cirurgia de enxerto de veia e randomizados para tratamento com veículo ou atorvastatina; quinze ratos foram submetidos à cirurgia sham. Detectamos a hiperplasia intimal por meio de coloração com hematoxilina-eosina e a expressão de proteínas relacionadas por meio de análise imuno-histoquímica e Western blot. Foram realizadas as comparações por análise de variância de fator único e pelo teste da diferença mínima significativa de Fisher, com p < 0,05 considerado significativo. Resultados: A íntima analisada pela coloração com hematoxilina-eosina era dramaticamente mais espessa no grupo controle que no grupo atorvastatina e no grupo sham (p < 0,01). Os resultados da coloração imuno-histoquímica de α-SMA demonstraram que a porcentagem de células positivas para α-SMA no grupo controle era mais alta que no grupo atorvastatina (p < 0,01). Nós também avaliamos α-SMA, PCNA, p38 MAPK e fosforilação de p38 MAPK após o tratamento com estatina por meio de análise de Western blot e os resultados indicaram que a atorvastatina não levou à redução de p38 MAPK (p < 0,05); no entanto, resultou na inibição da fosforilação de p38 MAPK (p < 0,01) e reduziu significativamente os níveis de α-SMA e PCNA, em comparação com o grupo controle (p < 0,01). Conclusão: Nós demonstramos que a atorvastatina pode inibir o acúmulo de células musculares lisas vasculares por meio da inibição da via p38 MAPK e é capaz de inibir a hiperplasia intimal em modelos de enxerto de veia em ratos. Abstract Background: The rate of saphenous vein graft failure one year after coronary artery bypass grafting ranges from 10% to 25%. The aim of this study was to explore whether atorvastatin can reduce accumulation of vascular smooth muscle cells to inhibit intimal hyperplasia via p38 MAPK pathway inhibition. Methods: Forty-five Sprague-Dawley rats were randomized to three groups. Thirty rats received a vein graft operation, and they were randomized to be treated with vehicle or atorvastatin; fifteen rats received a sham operation. We detected intimal hyperplasia by hematoxylin-eosin staining and related protein expression by immunohistochemical and Western blot analysis. Comparisons were analyzed by single-factor analysis of variance and Fisher's least significant difference test, with p < 0.05 considered significant. Results: The intima analyzed by hematoxylin-eosin staining was dramatically thicker in the control group than in the atorvastatin group and sham group (p < 0.01). The outcomes of immunohistochemical staining of α-SMA demonstrated that the percentage of α-SMA-positive cells in the control group was higher than in the atorvastatin group (p < 0.01). We also evaluated α-SMA, PCNA, p38 MAPK, and phosphorylation of p38 MAPK after statin treatment by Western blot analysis, and the results indicated that atorvastatin did not lead to p38 MAPK reduction (p < 0.05); it did, however, result in inhibition of p38 MAPK phosphorylation (p < 0.01), and it significantly reduced α-SMA and PCNA levels, in comparison with the control group (p < 0.01). Conclusion: We have demonstrated that atorvastatin can inhibit accumulation of vascular smooth muscle cells by inhibiting the p38 MAPK pathway, and it is capable of inhibiting intimal hyperplasia in a rat vein graft model.

Edge computing is a promising technology to empower the Internet of Things (IoT) by providing additional processing ability, where the tasks can be offloaded to the edge servers for efficient computing. To enable easy management and improve the resource utilization of edge computing, network function virtualization (NFV) is often employed to quickly deploy the requested network functions (NFs) for serving front-end devices. Considering that the edge servers are close to the front-end users, the time-varying geographical distribution of users has a significant influence on the NF deployment in the network of edge servers. Based on this observation, we propose a deep-reinforcement-learning (DRL)-based approach for the NF deployment, which has the following two salient features. First, we employ DRL to estimate the underlying wireless features affected by user mobility, which has a direct impact on the task performance in the edge-IoT systems. Second, we implicitly utilize the multiaccess opportunity to deploy the NFs, considering the estimated features and user requests. Compared to the existing works, the proposed work can significantly improve the resource utilization of edge servers as well as the computational efficiency of IoT tasks. The evaluation results obtained from extensive simulation experiments show that our approach can be well adapted to the time-varying user geodistributions and achieve improved performance in terms of both resource utilization of edge servers and task executions of the IoT devices.

Multichannel communication is an important means to improve the reliability of low-power Internet-of-Things (IoT) networks. Typically, data transmissions in IoT networks are often required to be delivered before a given deadline, making deadline-driven channel allocation an essential task. The existing works on time-division multiple access often fail to establish channel schedules to meet the deadline requirement, as they often assume that transmissions can be successful within one transmission slot. Besides, the allocation and link estimation incur considerable overhead for the IoT nodes. In this article, we propose an edge-based channel allocation (ECA) for unreliable IoT networks. In ECA, we explicitly consider the impact of allocation sequences and employ a recurrent-neural-network-based channel estimation scheme. We utilize link quality and retransmission opportunities to maximize the packet delivery ratio before deadline. The allocation algorithms are executed on edge servers such that: 1) the channel allocation can be updated more frequently to deal with the wireless dynamics; 2) the allocation results can be obtained in real time; and 3) channel estimation can be more accurate. Extensive evaluation results show that ECA can significantly improve the reliability of deadline-driven IoT networks.

Pelvic organ prolapse (POP) is a common symptom of pelvic floor disorders which is characterized by the descent of the uterus, bladder or bowel from their normal anatomical position towards or through the vagina. Among the older population, the incidence of POP increases with age. It is becoming necessary to recognize that POP is a degenerative disease that is correlated with age. In recent years, studies have been performed to improve understanding of the cellular and molecular mechanisms concerning senescent fibroblasts in pelvic tissues, which contribute to the loss of structure supporting the pelvic organs. These mechanisms can be classified into gene and mitochondrial dysfunctions, intrinsic senescence processes, protein imbalance and alterations in stem cells. The present review provides an integrated overview of the current research and concepts regarding POP, in addition to discussing how fibroblasts can be targeted to evade the negative impact of senescence on POP. However, it is probable that other mechanisms that can also cause POP exist during cell senescence, which necessitates further research and provides new directions in the development of novel medical treatment, stem cell therapy and non‑surgical interventions for POP.

Pelvic floor disorders (PFDs) represent a group of common and frequently-occurring diseases that seriously affect the life quality of women, generally including stress urinary incontinence and pelvic organ prolapse. Surgery has been used as a treatment for PFD, but almost 30% of patients require subsequent surgery due to a high incidence of postoperative complications and high recurrence rates. Therefore, investigations of new therapeutic strategies are urgently needed. Stem cells possess strong multi-differentiation, self-renewal, immunomodulation, and angiogenesis abilities and they are able to differentiate into various cell types of pelvic floor tissues and thus provide a potential therapeutic approach for PFD. Recently, various studies using different autologous stem cells have achieved promising results by improving the pelvic ligament and muscle regeneration and conferring the tissue elasticity and strength to the damaged tissue in PFD, as well as reduced inflammatory reactions, collagen deposition, and foreign body reaction. However, with relatively high rates of complications such as bladder stone formation and wound infections, further studies are necessary to investigate the role of stem cells as maintainers of tissue homeostasis and modulators in early interventions including therapies using new stem cell sources, exosomes, and tissue-engineering combined with stem cell-based implants, among others. This review describes the types of stem cells and the possible interaction mechanisms in PFD treatment, with the hope of providing more promising stem cell treatment strategies for PFD in the future.

Driven by the tremendous application demands, the Internet of Things (IoT) systems are expected to fulfill computation-intensive and latency-sensitive sensing and computational tasks, which pose a significant challenge for the IoT devices with limited computational ability and battery capacity. To address this problem, edge computing is a promising architecture where the IoT devices can offload their tasks to the edge servers. Current works on task offloading often overlook the unique task topologies and schedules from the IoT devices, leading to degraded performance and underutilization of the edge resources. In this article, we investigate the problem of fine-grained task offloading in edge computing for low-power IoT systems. By explicitly considering: 1) the topology/schedules of the IoT tasks; 2) the heterogeneous resources on edge servers; and 3) the wireless interference in the multiaccess edge networks, we propose a lightweight yet efficient offloading scheme for multiuser edge systems, which offloads the most appropriate IoT tasks/subtasks to edge servers such that the expected execution time is minimized. To support the multiuser offloading, we also propose a distributed consensus algorithm for low-power IoT devices. We conduct extensive simulation experiments and the results show that the proposed offloading algorithms can effectively reduce the end-to-end task execution time and improve the resource utilization of the edge servers.

Recent advances in microelectronic technologies have enabled the design and proliferation of low-power wireless networks for autonomously monitoring and control of wireless healthcare systems. In order to control and update the network nodes (e.g., bug fixing, command distribution, software update) in the healthcare system, reliable and efficient data dissemination is one of the key building blocks. However, traditional data dissemination relies mainly on the Internet of Things (IoT) nodes and thus much energy is wasted. With the development of 5G communication technologies, especially the mobile edge computing (MEC), it is believed that the edge server will become promising and more pervasively deployed. Despite computational offloading, the edge servers are also capable of communicational offloading. Therefore, to achieve data dissemination in an efficient way, we propose an edge-aided data dissemination system, in which the mobile edge servers are used to disseminate different segments of data objects. After that, IoT nodes exchange segments with each other to collect the entire data objects. In our work, we design the installation mechanism and data propagation protocol to not only ensure integrality of the data objects transmitted but also avoid the transmission conflicts. Furthermore, we design an adaptive protocol to achieve efficient data dissemination for heterogeneous IoT networks. We conduct extensive experiments and large-scale simulations. The results demonstrate that with the help of mobile edge servers, the energy efficiency is significantly improved compared to traditional dissemination approaches.

Federated learning (FL) has been employed for numerous privacy-sensitive applications, where distributed devices collaboratively train a global model. In industrial Internet of things (IIoT) systems, training latency is the key performance metric as the automated manufacture usually requires timely processing. The existing works increase the number of effective devices to accelerate the training. However, devices in IIoT systems are usually deployed densely; increasing the number of clients can potentially cause serious interference and prolonged training latency. In this article, we propose a resource allocation scheme for FL, namely RaFed . We formulate the problem of reducing training latency as an optimization problem, which is proved to be NP-hard. We propose a heuristic algorithm to select appropriate devices for achieving a good tradeoff between the interference and convergence time. We conduct experiments using an RGB-D dataset in an IIoT system. The results show that RaFed significantly reduces the latency by 29.9%, compared to the state-of-the-art works.

Timely prediction of the mechanism and characteristics of chronic liver disease using next-generation information technology is an effective way to improve the diagnosis rate of chronic liver disease. In this paper, we have proposed a modified backpropagation (BP) neural network with improved ant colony optimization algorithm to process multiple index attribute items describing chronic liver disease and construct a chronic liver disease assessment model. The proposed model is very effective in detecting chronic liver disease on time with acceptable level of accuracy and precision ratio. To verify these claims, the proposed scheme is checked experimentally where 125 groups of 20-dimensional medical test index data items of patients with chronic liver disease were analyzed. Moreover, 13-dimensional index items were preferentially selected as test index attribute items with high sensitivity to chronic liver disease using well-known ROC curves. The 13-dimensional index items were reduced to 5-dimensional comprehensive data items by principal component analysis. The proposed neural network-based model was trained with 115 sets of test indicator sample sets, and the remaining 10 sets of sample sets were used as test samples. Compared with the original 20-dimensional data as the neural network input, the proposed model not only reduces the complexity but also improves the prediction accuracy by 15.07%.

Content Caching at the edge of vehicular networks has been considered as a promising technology to satisfy the increasing demands of computation-intensive and latency-sensitive vehicular applications for intelligent transportation. The existing content caching schemes, when used in vehicular networks, face two distinct challenges: 1) Vehicles connected to an edge server keep moving, making the content popularity varying and hard to predict. 2) Cached content is easily out-of-date since each connected vehicle stays in the area of an edge server for a short duration. To address these challenges, we propose a Mobility-aware Proactive edge Caching scheme based on Federated learning (MPCF). This new scheme enables multiple vehicles to collaboratively learn a global model for predicting content popularity with the private training data distributed on local vehicles. MPCF also employs a Context-aware Adversarial AutoEncoder to predict the highly dynamic content popularity. Besides, MPCF integrates a mobility-aware cache replacement policy, which allows the network edges to add/evict contents in response to the mobility patterns and preferences of vehicles. MPCF can greatly improve cache performance, effectively protect users’ privacy and significantly reduce communication costs. Experimental results demonstrate that MPCF outperforms other baseline caching schemes in terms of the cache hit ratio in vehicular edge networks.

The combination of polymer and nanoparticles can create unique physicochemical properties, which is expected to be applied in the field of photodetection. Studies have found that synthetic polymer polyvinyl alcohol (PVA) can passivate nanoparticles and enhance the optical properties of the composite. In this paper, carbon nanodots (CNDs) mixed with PVA were used as the active layer film to prepare a metal–semiconductor–metal (MSM)-structured solar-blind ultraviolet (UV) photodetector. The responsivity and external quantum efficiency reached 267.1 mAW−1 and 158%, respectively. Compared with pure CNDs’ photodetector, the photocurrent of the PVA/CNDs’ photodetector was obviously improved. The enhanced performance could be attributed to the surface passivation by PVA, which modified surface functional groups of CNDs and attenuated the H2O absorption on the film surface. Moreover, the concentration of the active layer had great influence of the photocurrent; the optimal volume ratio of CNDs to PVA was 2.2% according to the comparison of the three devices with different concentrations. This work provided a promising way to fabricate high-performance, low-cost solar-blind UV photodetectors.

Rheumatoid arthritis (RA) is a common autoimmune disease in the elderly and it has been recently reported to be significantly associated with the activation of mast cells in joint tissues. IL-17A is a vital mediator that stimulates the activation of inflammation. Allopurinol is a classic agent for the suppression of uric acid production, recently reported to exert therapeutic effects on RA. In the present study, we investigated the regulatory effect of allopurinol against IL-17A-induced inflammatory response in mast cells and explored the potential mechanism of allopurinol on RA treatment. Firstly, we found that compared to normal synovium, IL-17A was significantly upregulated in the human RA synovium. IL-17A was used to stimulate an inflammatory state in mast cells in the absence or presence of allopurinol. We found that the production of inflammatory factors, PGE2, and COX-2 was significantly elevated in IL-17A-treated mast cells, accompanied by the activation of the iNOS/NO axis and the elevated secretion of ROS. After treatment with allopurinol, the elevated inflammation, activated COX-2/PGE2 and iNOS/NO axis, and oxidative stress were all dramatically alleviated. Mechanistically, the activated JNK/AP-1 and NF-κB pathways in IL-17A-treated mast cells were dramatically suppressed by the introduction of allopurinol. Taken together, our data reveal that allopurinol significantly alleviated the IL-17A-induced inflammatory response in mast cells.

Background: Quantification of cardiac structure and function is essential for diagnostic interpretation and clinical decision making. We sought to establish cardiovascular magnetic resonance (CMR) reference values of left and right ventricular (LV and RV) morphology and function based on a large sample of healthy Chinese adults.Methods: Five hundred fifty validated healthy Chinese adults (aged 21–70 years; 323 men) free of hypertension, diabetes, and obesity were included in this study. All the subjects were stratified by gender (men and women) and age decades. On cine CMR, measurements of biventricular end-diastolic, end-systolic, and stroke volumes (EDV, ESV, and SV), ejection fraction (EF), and end-diastolic LV wall thickness (LVWT) and mass (LVM) were obtained.Results: Men had greater LVEDV (111.6 ± 19.8 vs. 94.6 ± 15.6 ml), LVESV (36.5 ± 9.8 vs. 28.2 ± 7.9 ml), LVM (121.1 ± 19.9 vs. 86.1 ± 14.5 g), global end-diastolic LVWT (8.1 ± 1.1 vs. 6.7 ± 1.0 mm), RVEDV (128.0 ± 23.6 vs. 101.7 ± 17.0 ml), and RVESV (53.5 ± 13.7 vs. 36.8 ± 8.9 ml), while women had greater LVEF (67.5 ± 5.4 vs. 70.4 ± 5.7%) and RVEF (58.5 ± 5.2 vs. 64.0 ± 5.3%) (all p < 0.001). For both men and women, age was negatively correlated with LVEDV (r = −0.31 and r = −0.32), LVESV (r = −0.37 and r = −0.47), RVEDV (r = −0.31 and r = −0.29), and RVESV (r = −0.33 and r = −0.44), while it was positively correlated with LVEF (r = 0.28 and r = 0.43) and RVEF (r = 0.28 and r = 0.41) (all p < 0.001). Aging was associated with increasing global end-diastolic LVWT and LVM/LVEDV in both sexes (all p < 0.001). Older age was associated with increasing LVM only in women (r = 0.36, p < 0.001), not in men (r = 0.05, p = 0.359).Conclusions: We systematically provide age-, sex-, and body size-specific CMR reference values for biventricular morphology and function based on a large sample of healthy Chinese adults. Biventricular structure and function are significantly associated with age and sex.

Background Whole-body diffusion-weighted imaging (WB-DWI) is a method for evaluating bone marrow infiltration in multiple myeloma (MM). This study seeks to elucidate the correlation between the apparent diffusion coefficient (ADC) value and some selected clinical parameters. Methods A total of 101 Chinese patients with MM who had undergone WB-DWI from May 2017 to May 2019 were enrolled in this study. The ADC values of the MM lesions and the clinical parameters were quantified at the first (baseline) visit and after four-course induction chemotherapy. Multiple linear regression and logistic analyses were carried out to find the implicit inherent relationships within the patients’ data. Results The paired Wilcoxon test showed that the ADC values at the baseline visit (ADC0) were significantly lower than the values after four-course induction chemotherapy (ADC4 c) (p p 0 was negatively associated with β2-MG (p p = 0.012), while the RISS Stage III (p = 0.001), type IgG λ (p = 0.005), and albumin were negatively associated with ADC4 c (p = 0.010). The impacts of the therapeutic response were associated with ADC0 and immunoglobulin heavy chain gene rearrangement (p Conclusion The ADC values of WB-DWI may be associated with clinical parameters of MM including the fluorescence in situ hybridization result, and may be useful in the prognosis of patients with MM. Trial Registration: ChiCTR2000029587

It is of great significance for the stability of power system to research the electromagnetic and mechanical dynamic characteristics of transformer in short-circuit fault by numerical simulation. A 110kV/25000kVA power transformer model is established by the finite element method. In which Ogden model is adopted to conduct simulation analysis on winding spacer for considering its nonlinear mechanical characteristics. Some simulation results are obtained on the basis of modeling. Firstly, the magnitude and distribution of the axial and radial electromagnetic force of windings in short-circuit fault are calculated. Secondly, the dynamic change rule of displacement and stress of high voltage and low voltage windings in short- circuit fault is obtained. Thirdly, the distribution of maximum displacement and maximum stress on each coil disk are calculated. In addition, the difference of mechanical characteristics between HV winding and LV winding is analyzed. The above results can provide reference for transformer design.

In core-shell nanowire (NW) networks, the electrical connectivity of nanoscale core-shell nanowire junction can be modulated for potential applications in modern electronic components, especially the resistive switching (RS) application. In this work, an Ag@TiO 2 core−shell structure was deliberately designed to fabricate a resistive switching device with an Ag/Ag@TiO 2 /Ag planar structure, in which the Ag core can act as metallic interconnect and the insulating TiO 2 shell acts as a switching medium to provide a conductive pathway for Ag filament migration. The device displays a volatile threshold resistive switching characteristic, and an on/off ratio of ~105 was achieved. This work provides a foundation for engineering core-shell Ag@TiO 2 nanowire network for RS devices.

BACKGROUND While reference values of left atrial (LA) deformation parameters in Western populations have been established, reference data in healthy Asian populations are limited. PURPOSE To establish age- and sex-specific reference values for LA strain and strain rate (SR) based on a large sample of healthy Chinese adults using magnetic resonance-feature tracking (MR-FT). STUDY TYPE Retrospective. POPULATION Four hundred and eight healthy Chinese adults (220 males, aged 43.5 ± 11.5 years; 188 females, aged 45.3 ± 12.8 years). FIELD STRENGTH/SEQUENCE 1.5 T/balanced steady-state free precession. ASSESSMENT Reservoir strain (es ), conduit strain (ee ), booster strain (ea ), peak positive SR (SRs), peak early negative SR (SRe), and peak late negative SR (SRa) were obtained by MR-FT. STATISTICAL TESTS We used Shapiro-Wilk test, Student's t-test, Mann-Whitney U-test, linear regression, and coefficient of determination (r2 ). RESULTS Women demonstrated significantly greater LA strain (es [%]: 44.0 ± 9.9 vs. 38.3 ± 8.7; ee [%]: 26.7 ± 8.0 vs. 22.3 ± 6.8; ea [%]: 17.3 ± 4.4 vs. 16.0 ± 3.8) and SR (SRs [/second]: 1.8 ± 0.5 vs. 1.6 ± 0.4; SRe [/second]: -2.5 ± 0.9 vs. -2.1 ± 0.7; SRa [/second]: -1.9 ± 0.6 vs. -1.8 ± 0.5) than men. For both sexes, aging was significantly associated with decreased es , SRs, ee , and SRe (r2 = 0.07, r2 = 0.05, r2 = 0.19, and r2 = 0.24 for men; r2 = 0.13, r2 = 0.11, r2 = 0.31, and r2 = 0.46 for women), and significantly increased ea (r2 = 0.03 and r2 = 0.05 for men and women). There was no significant correlation between age and SRa in both sexes (P = 0.057 and P = 0.377 for men and women, respectively). DATA CONCLUSION We provide age- and sex-specific reference values for LA strain and SR based on a large sample of healthy Chinese adults using MR-FT. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 5.

The Internet of Things (IoT) and Industrial 4.0 bring enormous potential benefits by enabling highly customised services and applications, which create huge volume and variety of data. However, preserving the privacy in IoT and Industrial 4.0 against re-identification attacks is very challenging. In this work, we considered three main data types generated in IoT: context data, continuous data, and media data. We first proposed a stream data anonymisation method based on k-anonymity for data collected by IoT devices; and then privacy enhancing techniques for both continuous data and media data were proposed for different IoT scenarios. The experiment results show that the proposed techniques can well preserve privacy without significantly affecting the utility of the data.

Zero-dimension (0-D) lead halide perovskite nanocrystals (NCs) have attracted a sight of interest in the field of optoelectronic devices due to their outstanding properties, such as high photoluminescence quantum yield (PLQY) and size- and composition-controlled tunable emission wavelengths. However, the toxicity of lead (Pb) element in the lead perovskite NCs is the bottleneck for the commercial application of perovskite NCs. Herein, we report a facile ligand-assisted synthesis to achieve lead-free Cs3Cu2Cl5 NCs with a high PLQY of ∼70% and good stability against environmental oxygen/moisture as a promising down-conversion material. It has good merits of high PLQY and large Stokes shift (∼300 nm) originated from the effect of Jahn–Teller distortion and self-trapped excitons (STEs). Furthermore, the Cs3Cu2Cl5 NCs embedded composite films (NCCFs) were utilized to enhance the ultraviolet (UV) response of silicon (Si) photodetectors. External quantum efficiency (EQE) measurements show that the UV response can be greatly improved from 3.3 to 19.9% @ 295 nm based on NCCFs combined with Si photodiodes. Our work offers an effective approach to develop highly efficient and stable lead-free Cs3Cu2Cl5 NCs for the application in the solar-blind UV photodetector.

Recent years, organic-inorganic hybrid perovskites (OIHPs) have been widely used in applications, such as solar cells, lasers, light-emission diodes, and photodetectors due to their outstanding optoelectronic properties. Nowadays photodetectors based on perovskite films (PFs) suffer from surface and interface traps, which result from low crystalline quality of perovskite films and lattice mismatch between perovskite films and substrates. Herein, we fabricate MAPbI3-(MA = CH3NH3) single-crystal films (SCFs) on MAPbBr3single crystal substrates in MAPbI3precursor solution during crystallization process via solution-processed epitaxy. Benefit from the good lattice matching, epitaxial MAPbI3SCFs with high crystallinity and smooth morphology are of comparable quality to MAPbI3PSCs and are of better quality than MAPbI3polycrystalline films. Here we report that epitaxial MAPbI3SCFs have a low trap density of 5.64×1011cm–3and a long carrier lifetime of 11.86 μs. In this work, photodetector based on epitaxial MAPbI3single-crystal film (SCF) exhibits an excellent stability of a long-term stable response after 120 days, a fast response time of 2.21 μs, a high responsivity of 1.2 A W–1and a high detectivity of 3.07 ×1012jones.

Network function virtualization (NFV) has been considered as a promising technology for future Internet to increase the network flexibility, accelerate the service innovation, and reduce the Capital Expenditures and Operational Expenditures costs through migrating network functions from dedicated network devices to commodity hardware. Recent studies reveal that although this migration of network function brings the network operation unprecedented flexibility and controllability, NFV-based architecture suffers from serious performance degradation compared with traditional service provisioning on dedicated devices. In order to achieve a comprehensive understanding of the service provisioning capability of NFV, this paper proposes a novel analytical model based on Stochastic Network Calculus (SNC) to quantitatively investigate the end-to-end performance bound of the NFV networks. To capture the dynamic and on-demand NFV features, both the non-bursty traffic, e.g., the Poisson process, and the bursty traffic, e.g., the Markov Modulated Poisson Process, are jointly considered in the developed model to characterize the arriving traffic. To address the challenges of resource competition and end-to-end NFV chaining, the property of convolution associativity and leftover service technologies of SNC are exploited to calculate the available resources of the Virtual Network Function nodes in the presence of multiple competing traffic and transfer the complex NFV chain into an equivalent system for performance derivation and analysis. Both the numerical analysis and extensive simulation experiments are conducted to validate the accuracy of the proposed analytical model. Results demonstrate that the analytical performance metrics match well with those obtained from the simulation experiments and numerical analysis. In addition, the developed model is used as a practical and cost-effective tool to investigate the strategies of the service chain design and resource allocations in the NFV networks.

Cyberspace security is vital to state interest. Recently, there are some challenges in cyber security. In architecture for instance, although protection mechanisms are introduced and applied everywhere, the modern network architecture (well connected and open) still has difficulty in completely ensuring cyber security. It is also observed that contemporary cyber security protection mechanism highly depends on the priori information of security threats and thus will hardly address unknown potential threats. In this paper, a novel cyberspace security protection framework is proposed. A dual-structural Internet scheme that integrates the current Internet architecture with a redundant secondary structure network characterized by its broad-storage scheme, heterogeneous structure, and dynamic protection mechanism is introduced. Also, a novel active defense mechanism that is knowledge-data driven and thus independent of the priori information of the security threat is proposed. Furthermore, some key techniques such as transparent access and prepositive active defense are introduced. The theoretical and technical work proposed in this paper offers a comprehensively evolutionary solution to constructing a cyberspace in which the protection mechanism is more independent and active.

The recent advances in microelectronics and communications have led to the development of large-scale Internet of Things (IoT) networks, where tremendous sensory data is generated and needs to be processed. To support real-time processing for large-scale IoT, deploying edge servers with storage and computational capability is a promising approach. In this paper, we carefully analyze the impacting factors and key challenges for edge node (EN) deployment. We then propose a novel three-phase deployment approach which considers both traffic diversity and the wireless diversity of IoT. The proposed work aims at providing real-time processing service for the IoT network and reducing the required number of ENs. We conducted extensive simulation experiments, the results show that compared to the existing works that overlooked the two kinds of diversities, the proposed work greatly reduces the number of ENs and improves the throughput between IoT and ENs.

Keyboard input is an important way to enter massive personal information into computing systems and the Internet in our social life. The large amount of acoustic data from the keystroke tapping makes it possible for eavesdroppers to snoop the sensitive and private input remotely. Keystroke monitoring using the acoustic signals, which extracts the user information directly from the keystroke acoustics, is a critical security and privacy issue and has recently attracted much research attention. The existing works use smartphones to collect and infer the keystrokes with various data analysis algorithms. However, most of them rely on the assumption that the phone-keyboard relative position is known in advance, which is often unrealistic for real-world scenarios such as adversary eavesdropping. To address this problem and make keystroke monitoring free to use, in this paper, we propose a Po sition free Ke ystroke Mon itoring scheme using a single smartphone. By exploiting the reliable linguistic accountings and the layout of a certain keyboard, we develop a geometrical approach to estimate the relative positions and angles of the smartphone to the keyboard. Our proposed scheme can self-calibrate the position estimation with the continuous acoustic signals. After that, effective keystroke snooping is established based on the Mel-Frequency Cepstral Coefficient and adaptive k -means clustering. We conduct experiments with Samsung S4 smartphones and simulations. The results show that the positioning scheme achieves a high accuracy by 93%, and the keystroke snooping accuracy is improved by 32.6% compared to the existing works.

Organic-inorganic hybrid methylammonium lead halide perovskite MAPbX3 (where MA = CH3NH3, and X = Cl, Br, I) single crystals are potential semiconductors for photo-detection due to their excellent optoelectronic performance. In particular, MAPbCl3 single crystal is a wide-band-gap (2.9 eV) semiconductor which is suitable for ultraviolet (UV) detection. In this work, n−-n+ photo-diodes are fabricated through solution-processed epitaxial growth, growing Bi-doped MAPbCl3 epitaxial layer on MAPbCl3 single crystal substrate. The epitaxial layer effectively improves the interface between n−-type and n+-type layers and leads to low dark current. This work provides useful information for UV detection based on perovskites.

Previously, Engineering maintenance vehicle mainly through human operations, which has higher labor costs and lower efficiency. In order to obtain complete images needed in the field of engineering maintenance quickly and easily, auto pilot of engineering maintenance vehicle can play a huge role in engineering fields such as power maintenance and highway maintenance. Automatic ground key information detection is the most important part of auto pilot of engineering maintenance vehicle. In this study, we propose a new model that uses an improved form of the You Only Look Once (YOLO) model to enhance the real-time detection of key information problems. This model is mainly realized by optimizing the network structure of original YOLOv3 model. The experimental results show that in the highway center marking data set, the precision of the trained model is 95.76%, and an average accuracy of 90.43% for the test setup. By comparing with YOLOv3, the detection accuracy of the proposed improved method is mainly improved. At the same time, under GPU acceleration, the average detection speed is 29.20 frames/s, which can meet the real-time detection by the engineering maintenance vehicle platform.

China's economy has experienced dramatic growth in the last 30 years and in relation to seafaring labour supply many expected that Chinese seafarers would eventually come to dominate the world seafarers' labour market. In fact, although the number of Chinese seafarers in the international fleet has grown steadily since the 1990s, the increase has been slower than many international shipping industry commentators and academics predicted (BIMCO/ISF 1995; Li and Wonham 1999; Sharma 2002; Wu 2004; Wu et al. 2007; Zhao 2017). China’s economy has experienced dramatic growth in the last 30 years and in relation to seafaring labour supply many expected that Chinese seafarers would eventually come to dominate the world seafarers’ labour market. In fact, although the number of Chinese seafarers in the international fleet has grown steadily since the 1990s, the increase has been slower than many international shipping industry commentators and academics predicted (BIMCO/ISF 1995; Li and Wonham 1999; Sharma 2002; Wu 2004; Wu et al. 2007; Zhao 2017).

In the study reported here, polylactic acid (PLLA) polymer was synthesized using stannous octoate (Sn(Oct)2) and N-(t-butoxycarbonyl) ethanolamine (EABoc) as the catalyst and the initiator, respectively. The selected PLLA polymer with proper molecular weight was used to prepare nanobubbles encapsulating with liquid perfluoropentane. Then, lactoferrin (Lf), which has a good affinity with tumor cells, was conjugated to PLLA nanobubbles. The resulting Lf–PLLA nanobubbles were examined from the perspective of appearance, size, zeta potential, and stability in vitro. The average hydrodynamic diameter of the Lf–PLLA nanobubbles was 315.3 ± 4.2 nm, the polydispersity index (PDI) was 0.153 ± 0.020, and the zeta potential was around −11.3 ± 0.2 mV. Under the transmission electron microscope (TEM), Lf–PLLA nanobubbles were highly dispersed and had a spherical shape with a distinct capsule structure. The Lf–PLLA nanobubbles also showed little cytotoxicity and low hemolysis rate and exhibited good stability in vitro. The enhanced ultrasound imaging ability of Lf–PLLA nanobubbles was detected by an ultrasound imaging system. The results of ultrasound studies in vitro showed that the liquid perfluoropentane underwent phase transition under ultrasonic treatment, which proved the Lf–PLLA nanobubbles could enhance the ability of ultrasonic imaging. The studies of ultrasonic imaging in nude mice bearing subcutaneous tumors showed that the ability of enhanced ultrasonic images was apparent after injection of Lf–PLLA nanobubbles. Acoustic behavior in vitro and in vivo showed that the Lf–PLLA nanobubbles were characterized by strong, stabilized, and the ability of tumor-enhanced ultrasound imaging. Thus, the Lf–PLLA nanobubbles are an effective ultrasound contrast agent for contrast-enhanced imaging.

Mobile crowd sensing (MCS), as a novel paradigm that coordinates a crowd of distributed devices to complete a whole sensing task, has attracted tremendous attention. While providing an effective and practical approach for sensing in largescale mobile scenes, the existing works on MCS suffer from a risk of privacy leakage because user data needs to be gathered in the cloud for processing and analysis. Federated Learning (FL) is a promising alternative as it can leverage mobile devices to accomplish a large learning task without centrally collecting the user data. However, incorporating FL into MCS is a non-trivial task due to the following reasons: 1) the data quality of mobile devices is often unreliable, especially in the context of crowd sensing; 2) the existing incentive mechanism in MCS may not work due to the lack of access to the user data. To address the problem, we propose a privacy-preserving mobile crowd sensing system based on Federated Learning with unreliable user data (called F-Sense). We analyze the key issues of sensing tasks, and further design an incentive mechanism to reward and motivate participants. Moreover, we explore to construct a federated quality model of user data in order to improve the data quality and obtain better training results for sensing tasks. Extensive simulation results show that F-Sense achieves privacy-preserving crowd sensing and the developed incentive mechanism can improve the task efficiency by encouraging local training at mobile devices.

With high time resolution and wide coverage, GF-4 camera can achieve high-frequency repeated monitoring over a wide range of areas within a certain period of time. However, there are some problems of its sequence images, such as shaking, non-prominent ship targets and insufficient brightness in sea area, which are not conducive to the detection of moving ships. Thus, a hierarchical registration algorithm combining SURF and SIFT, and an image enhancement algorithm combining wavelet threshold denoising and Top-hat filtering was proposed to solve these problems. Matlab’s experiment proves that the processed image can almost only contain the highlighted target and the black background, which improves the accuracy of subsequent ship monitoring.

The data privacy concerns are increasingly affecting the Internet of things (IoT) and artificial intelligence (AI) applications, in which it is very challenging to protect the privacy of the underlying data. In recent, the advancements in the performances of homomorphic encryption (HE) make it possible to help protect sensitive and personal data in IoT applications using homomorphic encryption based schemes. This paper proposed a practical homomorphic encryption scheme that can enable data users in IoT systems to securely operate data over encrypted data, which can effectively protect the privacy of key data in the system. The experimental results demonstrated the effectiveness proposed scheme.

The energy internet is a multi-energy sharing system with the coordinated and optimized operation of "source-network-load-storage". The energy router (ER) is the basic equipment in the future energy internet, so the research on the routing strategy of the ER is of great significance for the energy optimization. The traditional routing strategy based on the minimum loss path (MLP) does not consider the loss cost of different distributed energy resources (DERs), so the DERs with low loss cost have the same transaction priority as the DERs with high loss cost. In addition, power exchange should not be limited to traditional centralized allocation and scheduling, but peer to peer (P2P) transactions between ERs. Therefore, a minimum loss cost path (MLCP) routing strategy that can realize P2P transactions is proposed, which can maximize the benefits and improve the priority of renewable energy by modifying marginal cost coefficient. At the same time, a scheme of congestion management based on "the principle of equal mini rate of loss" is presented, which has less loss cost and can obtain the best optimization effect under the condition of critical congestion. Effectiveness of MLCP routing strategy is proved by simulation, and the superiority of the congestion management scheme is verified by comparing with traditional schemes.

LoRa has attracted much research attention due to its long communication range and low power consumption on end devices. In LoRa networks, the energy consumption on the end devices can be unfair, because some end devices have to use large spreading factors (leading to long transmission time) or large transmission power to reach a far-away gateway, and their energy consumption can be quite different. As a result, these end devices will run out of their batteries much faster, which may significantly reduce the network lifetime. The existing works have focused on the static resource allocation in LoRa networks to achieve energy fairness. However, due to the dynamic wireless environment, the static allocation can be inefficient in practice. In this paper, we develop AdapLoRa, a lifetime-aware dynamic network resource allocation system, to maximize the network lifetime of LoRa networks. AdapLoRa periodically adapts the resource allocation according to the link quality of end devices. A fine-grained network model is developed to capture the link quality variations and network interference. Finally, by considering the adaptation overhead (e.g., energy consumed by end devices to receive the configuration commands), we propose to gradually improve the network lifetime by periodically estimating network lifetime with different resource allocations. We implement AdapLoRa on a LoRa testbed, and the experimental results reveal that AdapLoRa improves the network lifetime by 23.7% compared with the state-of-the-art works.

X-ray photodiodes made of metal halide perovskites (MHPs) which directly convert X-ray photons into electron-hole pairs have shown advantages in low-cost and high X-ray detection sensitivity. However, devices fabricated by spin-coating and evaporation methods suffer from high traps density near poor interfacial layers (n-type/intrinsic and p-type/intrinsic) which lead to high dark current and noise current under large reverse bias. In this work, solution-processed doped epitaxial growth is employed to limit these traps through epitaxially growing n-type MHPs (bismuth-doped) and p-type MHPs (silver-doped) on opposite faces of intrinsic CH3NH3PbBr2.5Cl0.5 MHP single crystals. Through energy structure design, effective electron/hole blocking layers could decrease the noise and dark current, these X-ray PIN photodiodes work under a large external electrical field, which enables a state-of-art response speed (fall) of 750 ns and a lowest detectable dose rate of 17.7 nGys-1(40 kVp). This work will motivate new strategies to fabricate high-performance devices based on perovskites using solution-processed methods. These founding also explore a new generation of low dose and high dynamic X-ray detectors based on MHPs.

The ever-increasing demand for light, thin, flexible, and small-sized smart electronics has developed a market for planar micro energy storage devices with high performance, flexibility, and robust integration, that is not mature yet. Here, a high-resolution patterned platinum (Pt) layer that can be designed/shaped as required is prepared by printing sacrificial patterns (SPs) using a commercial laser printer. MnO2-based micro-supercapacitors (MSCs) are successfully prepared on commercial Polyethylene terephthalate (PET) via electrodeposition. Because of the large surface area and large number of active sites of the nano-branch-shaped MnO2, the MnO2/Pt MSCs exhibit excellent volumetric specific capacitance (615.14F cm−3) as well as an ultrahigh volumetric power density (11.677 Wh cm−3) and energy density (54.679 mWh cm−3). In addition, the MnO2/Pt MSCs possess excellent flexibility and integration, with capacitance retention when bend to 180° and can be designed to connect in series or parallel for delivering the desired output voltage and capacitance. Furthermore, planar Zn-MnO2 batteries are successfully prepared through step-by-step electrodeposition. Simultaneously, a flexible energy conversion storage system is constructed by connecting solar cells and electrical appliances with the fabricated MSCs, demonstrating that this straightforward strategy is extremely promising for future application in microcircuits and flexible wearable smart textiles.

Organic-inorganic hybrid perovskite single crystals (PSCs) have been emerged as remarkable materials for some optoelectronic applications such as solid-state photodetectors, solar cells and light emitting diodes due to their excellent optoelectronic properties. To decrease the dark current, function layers based on spin-coating method are frequently requested for intrinsic PSCs to block the injected current by forming energy barrier. However, the amorphous function layers suffer from small carrier mobility and high traps density, which limit the speed of the photoelectric response of perovskite devices. This work supposes to grow thick MAPbBr3 and MAPbI3 mono-crystalline thin films on the surface of intrinsic MAPbBr2.5Cl0.5 PSCs substrate by a heteroepitaxial growth technique to act as electron-blocking layers. Meanwhile, C60 and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) layers are deposited on the opposite surface of substrate PSCs by spin-coating method to block injected holes. This Au-MAPbI3-MAPbBr3-MAPbBr2.5Cl0.5PSCs-C60-PCBM-Ag heterostructure can be used as excellent X-ray photodetector (XPD) due to its low dark current density of 6.97 × 10−11 A cm−2 at −0.5 V bias, high responsivity of 870 mA/W at −100 V bias and X-ray sensitivity as high as 59.7 μC mGy−1 cm−2 at −50 V bias.