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Abstract Owing to the advantages of low cost, flexibility, and the transmission characteristics of air–ground (AG) channels, using the unmanned aerial vehicle (UAV) as mobile relay to assist wireless communication has received significant interest recently. A green non‐orthogonal multiple access (NOMA)‐based multi‐UAV‐enabled relaying system with different rate requirements is proposed here. To improve energy efficiency (EE) of the UAV relays, an optimization problem for user grouping, UAV trajectory design and resource allocation under the constraints of information causality constraint, UAVs' maximum service capacity, maximum transmit power constraint, and different communication rate requirements of the mobile users (MUs) is formulated. According to the grouping results, the UAVs' trajectory and power allocation by Dinkelbach method, successive convex approximation, and condensation algorithm are alternately optimized. To solve this highly coupled non‐linear mixed integer programming problem, a graph‐based grouping algorithm is proposed to reduce the relative distance between the UAV relay and the MU. Simulation results show that the proposed optimization algorithm can effectively improve the EE performance of this NOMA‐based multi‐UAV‐enabled relaying system.

Abstract This paper studies unmanned aerial vehicle (UAV)‐assisted cognitive network, where the UAV can improve the communication quality of edge users. Short packet communication (SPC) is widely used due to its low delay transmission characteristic. Unlike long packet communication in conventional wireless networks, SPC has a non‐negligible packet error rate and its data transmission rate is less than Shannon capacity. Considering the fact that the UAV is usually powered by battery, the energy efficiency (EE) maximisation problem is investigated based on short packet transmission in the UAV‐assisted cognitive network. Firstly, the closed‐form expression of EE is analysed, and then the optimisation problem is formulated by jointly optimising the spectrum sensing time, packet error rate, the flight speed, and the coverage range of UAV. Secondly, the optimisation problem is solved by dividing it into four subproblems. Then, an efficient iterative algorithm is proposed to tackle this problem. Simulation results show that the proposed optimisation scheme can evidently improve the EE performance compared with other benchmark schemes. In addition, the proposed joint optimisation algorithm not only has better convergence than exhaustive method, but also has higher stability than PSO algorithm.

Abstract With an increasing frequency of natural disasters and security attacks, the safe and stable operation of smart grid has been challenged unprecedently. To reduce the economic loss and social impact caused by power outage accidents, it is urgent to develop and improve the smart grid technology, and strengthen the disaster resistance and recovery capability of smart grids when faced with extreme events. As an efficient and flexible secondary energy source, hydrogen is crucial in improving the resilience of smart grid and supporting energy security. To further promote the deep integration of hydrogen systems and smart grid and improve the energy system resilience, the resilience of smart grids supported by hydrogen is assessed in this study. First, a technical framework of hydrogen‐powered smart grid resilience is established, and the value of hydrogen‐powered smart grid resilience is analysed considering different time frames (before, during and after an extreme event) of smart grids facing extreme events. Then, hydrogen‐powered smart grid resilience is investigated from perspectives of pre‐prevention regulation, in‐process correction regulation, and post‐recovery regulation. Finally, future direction for hydrogen‐powered smart grid resilience is investigated and related policy suggestions are provided.

Abstract Background Small extrachromosomal circular DNAs (eccDNAs) have the potential to be cancer biomarkers. However, the formation mechanisms and functions of small eccDNAs selected in carcinogenesis are not clear, and whether the small eccDNA profile in the plasma of cancer patients represents that in cancer tissues remains to be elucidated. Methods A novel sequencing workflow based on the nanopore sequencing platform was used to sequence naturally existing full‐length small eccDNAs in tissues and plasma collected from 25 cancer patients (including prostate cancer, hepatocellular carcinoma and colorectal cancer), and from an independent validation cohort (including 7 cancer plasma and 14 healthy plasma). Results Compared with those in non‐cancer tissues, small eccDNAs detected in cancer tissues had a significantly larger number and size (P = 0.040 and 2.2e‐16, respectively), along with more even distribution and different formation mechanisms. Although small eccDNAs had different general characteristics and genomic annotation between cancer tissues and the paired plasma, they had similar formation mechanisms and cancer‐related functions. Small eccDNAs originated from some specific genes had great multi‐cancer diagnostic value in tissues (AUC ≥ 0.8) and plasma (AUC > 0.9), especially increasing the accuracy of multi‐cancer prediction of CEA/CA19‐9 levels. The high multi‐cancer diagnostic value of small eccDNAs originated from ALK&ETV6 could be extrapolated from tissues (AUC = 0.804) to plasma and showed high positive predictive value (100%) and negative predictive value (82.35%) in a validation cohort. Conclusions As independent and stable circular DNA molecules, small eccDNAs in both tissues and plasma can be used as ideal biomarkers for cost‐effective multi‐cancer diagnosis and monitoring.

Abstract A solid‐state electrolyte (SSE), which is a solid ionic conductor and electron‐insulating material, is known to play a crucial role in adapting a lithium metal anode to a high‐capacity cathode in a solid‐state battery. Among the various SSEs, the single Li‐ion conductor has advantages in terms of enhancing the ion conductivity, eliminating interfacial side reactions, and broadening the electrochemical window. Covalent organic frameworks (COFs) are optimal platforms for achieving single Li‐ion conduction behavior because of well‐ordered one‐dimensional channels and precise chemical modification features. Herein, we study in depth three types of Li‐carboxylate COFs (denoted LiOOC‐COFn, n = 1, 2, and 3) as single Li‐ion conducting SSEs. Benefiting from well‐ordered directional ion channels, the single Li‐ion conductor LiOOC‐COF3 shows an exceptional ion conductivity of 1.36 × 10−5 S cm−1 at room temperature and a high transference number of 0.91. Moreover, it shows excellent electrochemical performance with long‐term cycling, high‐capacity output, and no dendrites in the quasi‐solid‐state organic battery, with the organic small molecule cyclohexanehexone (C6O6) as the cathode and the Li metal as the anode, and enables effectively avoiding dissolution of the organic electrode by the liquid electrolyte.

Abstract Integrated energy‐generating and storage films are able to convert mechanical force into stored electrical energy, with the potential for use in self‐powered wearable electronics and flexible energy supplies. The development of a transparent metal salt/polyvinylidene fluoride–hexafluoropropylene composite film is reported that possesses excellent piezoelectric and dielectric properties and has the potential to be employed as an energy‐generating and preserving integrated film. The effects of the type of the metal salt and its content on the dielectric properties, d33 value, open circuit voltage, and holding time of the composite films were investigated. Owing to the presence of pure water, the β‐phase composition and polarization of the film are increased, leading to improved energy conversion properties. Most important, the prepared film exhibits excellent light transmittance. This film, which possesses both good electrical and transparent properties, has the potential for use as a flexible energy supplier, particularly for photovoltaic devices.

Abstract Covalent organic frameworks (COFs) show considerable attention and potential value in energy storage and conversion. However, design and preparation novel dual‐active‐center modified COFs for high‐performance Li storage and accelerating Li diffusion are still challengeable. In this work, we synthesize dual‐active‐group of CN and CO decorated COF (denoted as Tp‐Ta‐COF) as the anode material for lithium‐ion batteries (LIBs). Benefiting from the dual‐active‐site, the Li+ diffusion kinetics on the Tp‐Ta‐COF are improved and Tp‐Ta‐COF electrode delivers high reversible capacity of 413 mAh g−1 under current density with 200 mA g−1. Moreover, 18 Li+ can be embed in Tp‐Ta‐COF with CN and CO containers. The mechanism between Li+ and active‐site is deeply deduced and studied by multiple in situ techniques and density functional theory (DFT) theoretical calculation, suggesting interactions of Li+ and active‐group are highly reversible procedures. Consequently, we expect this work could create a universal strategy for construction high‐performance Li storage COF‐based materials.

Abstract Aims Implantable device‐based sensor measurements including heart sounds, markers of ventilation, and thoracic impedance have been shown to predict heart failure (HF) hospitalizations. We sought to assess how these parameters changed prior to COVID‐19 (Cov‐19) and how these compared with those presenting with decompensated HF or pneumonia. Methods and results This retrospective analysis explores patterns of changes in daily measurements by implantable sensors in 10 patients with Cov‐19 and compares these findings with those observed prior to HF (n = 88) and pneumonia (n = 12) hospitalizations from the MultiSENSE, PREEMPT‐HF, and MANAGE‐HF trials. The earliest sensor changes prior to Cov‐19 were observed in respiratory rate (6 days) and temperature (5 days). There was a three‐fold to four‐fold greater increase in respiratory rate, rapid shallow breathing index, and night heart rate compared with those presenting with HF or pneumonia. Furthermore, activity levels fell more in those presenting with Cov‐19, a change that was often sustained for some time. In contrast, there were no significant changes in 1st or 3rd heart sound (S1 and S3) amplitude in those presenting with Cov‐19 or pneumonia compared with the known changes that occur in HF decompensation. Conclusions Multi‐sensor device diagnostics may provide early detection of Cov‐19, distinguishable from worsening HF by an extreme and fast rise in respiratory rate along with no changes in S3.

Abstract Aims This study aims to characterize the range of implantable device‐based sensor values including heart sounds, markers of ventilation, thoracic impedance, activity, and heart rate for patients with heart failure (HF) when patients were deemed to be in clinically stable periods against the time course of acute decompensation and recovery from HF events. Methods and results The MultiSENSE trial followed 900 patients implanted with a COGNIS CRT‐D for up to 1 year. Chronic, ambulatory diagnostic sensor data were collected and evaluated during clinically stable periods (CSP: unchanged NYHA classification, no adverse events, and weight change ≤2.27 kg), and in the timeframe leading up to and following HF events (HF admissions or unscheduled visits with intravenous HF treatment). Physiologic sensor data from 1667 CSPs occurring in 676 patients were compared with those data leading up to and following 192 HF events in 106 patients. Overall, the mean age was 66.6 years, and the population were predominantly male (73%). Patients were primarily in NYHA II (67%), with a mean LVEF of 29.6% and median NT‐proBNP of 754.5 pg/mL. Sensor values during CSP were poorer in patients who had HF events during the study period than those without HF events, including first heart sound (S1: 2.18 ± 0.84 mG vs. 2.62 ± 0.95 mG, P = 0.002), third heart sound (S3: 1.13 ± 0.36 mG vs. 0.91 ± 0.30 mG, P

Nanoparticle production and functionalization for various biomedical uses are still challenging. Polymer composites constituted of poly(amidoamine) (PAMAM), polyallylamine hydrochloride (PAH), and calcium carbonate (CaCO3) nanoparticles have good biocompatibility with physiological tissue and fluids, making them excellent candidates for biomedical applications. This study investigated the characteristics of polymeric/nano-CaCO3 composite films based on a PAH/PAMAM matrix, which were fabricated through layer-by-layer synthesis on quartz glass substrates. It was found that the as-prepared elastic moduli of the resultant (PAH/PAMAM)n-CaCO3 (where n represents the number of bilayers) composite films varied from 1.40 to 23.70 GPa for different degrees of cross-linking when 0.1 M nano-CaCO3 particles were incorporated into the polymer matrix. The highly cross-linked (PAH/PAMAM)15-CaCO3 composite film had the highest recorded elastic modulus of 23.70 GPa, while it was observed that for all the composite films fabricated for the present study, the addition of the nano-CaCO3 particles approximately doubled the elastic modulus regardless of the degree of polymerization. Live/Dead assays were used to determine whether the produced composite films were compatible with human lung fibroblast cells. The findings indicate that the (PAH/PAMAM)7.5-CaCO3 composite film had the most positive effect on cell growth and proliferation, with the (PAH/PAMAM)15-CaCO3 composite film demonstrating significant ion transport behavior with low impedance, which was considered good for in vivo rapid cell-to-cell communication. Therefore, the (PAH/PAMAM)7.5-CaCO3 and (PAH/PAMAM)15-CaCO3 composite films are potential tissue engineering biomaterials, but further studies are essential to generate more data to evaluate the suitability of these composites for this and other biomedical functions.

Abstract Introduction Postoperative delirium is one of the most common and dangerous psychiatric complications after hip surgery. The aim of this study was to investigate the incidence of postoperative delirium in elderly patients after hip fracture surgery and to identify risk factors for such, as part of developing a risk stratification index (RSI) system to predict a patient's risk of postoperative delirium. Methods Elderly patients (aged 65 years or older) with hip fractures who had received surgical treatment in our hospital between March 2018 and December 2019 were retrospectively included. Clinical data were collected, and multivariate logistic regression analysis was performed to investigate the relevant risk factors of postoperative delirium. An RSI system was developed based on factors identified in the regression analysis. Results Of 272 patients included, 52 (19.12%) experienced postoperative delirium. Drinking history (> 3/ week), the perioperative lactic acid level (Lac > 2 mmol/L), postoperative visual analog score (VAS) > 3, American Society of Anesthesiologists (ASA) physical status > II, application of the bispectral index, and preoperative diabetes were independent risk factors of postoperative delirium. When RSI ≥ 5, the rate of postoperative delirium significantly increased (p

The original target tracking algorithm based on a single model has long been unable to meet the complex and changeable characteristics of the target, and then there are problems such as poor tracking accuracy, target loss, and model mismatch. The interactive multimodel algorithm uses multiple motion models to track the target, obtains the degree of adaptation between the actual motion state of the target and each model according to the calculated likelihood function, and then combines the updated weight values of each filter to obtain a weighted sum. Therefore, the interactive multimodel algorithm can achieve better performance. This paper proposes an improved interactive multimodel algorithm that can achieve player tracking and trajectory feature matching. First, this paper proposes an improved Kalman filtering (IKF) algorithm. This method is developed from the unbiased conversion measurement Kalman filter, which can obtain more accurate target state and covariance estimation. Secondly, using the parallel processing mode of the IMM algorithm to efficiently solve the data association between multiple filters, the IMM-IKF model is proposed. Finally, in order to solve the problem of low computational efficiency and high mismatch rate in image feature point matching, a method of introducing a minimum spanning tree in two-view matching is proposed. Experimental results show that the improved IMM-IKF algorithm can quickly respond to changes in the target state and can find the matching path with the lowest matching cost. In the case of ensuring the matching accuracy, the real-time performance of image matching is ensured.

Studying the structure and evolution characteristics of social networks is of great significance in assessing and controlling the outbreak of infectious diseases. Therefore, it is necessary to find research trends in this field. In this study, 1,752 documents (2001–2020) related to the relationship between the social network and epidemic published from Scopus, WOS (Web of Science), and CNKI (China National Knowledge Infrastructure) databases were studied to provide a more comprehensive overview of the frontiers of research in this field, including epidemics in social networks, spread of disease, influence of different factors on the spread of the epidemic, prevention and control strategies of the epidemic, and comparison of various strategies. Besides, several new research directions in this field worthy of attention of researchers are discussed.

Extracorporeal circulation (ECC) is necessary for conventional cardiac surgery and life support, but it often triggers systemic inflammation that can significantly damage tissue. Studies of ECC have been limited to large animals because of the complexity of the surgical procedures involved, which has hampered detailed understanding of ECC-induced injury. Here we describe a minimally invasive mouse model of ECC that may allow more extensive mechanistic studies. The right carotid artery and external jugular vein of anesthetized adult male C57BL/6 mice were cannulated to allow blood flow through a 1/32-inch external tube. All animals (n=20) survived 30 min ECC and subsequent 60 min observation. Blood analysis after ECC showed significant increases in levels of tumor necrosis factor α, interleukin-6, and neutrophil elastase in plasma, lung, and renal tissues, as well as increases in plasma creatinine and cystatin C and decreases in the oxygenation index. Histopathology showed that ECC induced the expected lung inflammation, which included alveolar congestion, hemorrhage, neutrophil infiltration, and alveolar wall thickening; in renal tissue, ECC induced intracytoplasmic vacuolization, acute tubular necrosis, and epithelial swelling. Our results suggest that this novel, minimally invasive mouse model can recapitulate many of the clinical features of ECC-induced systemic inflammatory response and organ injury.