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Abstract Background The epidemiology of fungi identified via next-generation sequencing in bronchoalveolar lavage fluid among patients with COVID-19 is unknown. Methods De-identified information, including age, SARS-CoV-2 reads and fungi from bronchoalveolar lavage fluid, were used to analysis. Results A total of 960 patients with COVID-19 were included. Gender was unknown in 38 patients, and 648 (70.3%) of the rest patients were male. For 876 patients with information on age, their mean ± standard age was 63.4 ± 21.3 years, with the minimum being 0.2 years and the maximum being 101 years. For all the patients, their median [interquartile range] SARS-CoV-2 reads were 26,038 [4421.5, 44,641.5]. The Aspergilli were identified in 159 (16.6%) patients, with Aspergillus fumigatus, Aspergillus flavus and Aspergillus niger in 103 (10.7%), 81 (8.4%) and 17 (1.8%), respectively. The Mucoraceae were identified in 14 (1.5%) patients. Pneumocystis jirovecii was identified in 65 (6.8%) patients, among whom 12 (18.5%) patients also had Aspergilli. The Cryptococcaceae and the Dematiaceae were also identified in some patients, including Cryptococcus in 11 (1.1%) patients. Conclusions In bronchoalveolar lavage fluid among patients with COVID-19, the Aspergilli were very commonly identified, as were the Mucoraceae, Pneumocystis jirovecii and Cryptococcus via next-generation sequencing.

In arid areas, biodegradable film has recently had the potential to replace polyethylene (PE) film to address plastic pollution. However, the positive effect of biodegradable film on soil moisture and salt control is weaker than that of PE film. Magnetized irrigation water technology is expected to compensate for this limitation. This study comprised a field experiment in 20212023 to study how two types of biodegradable film (M1, black; M2, transparent) and six magnetization intensity on irrigation water (T0, 0 Gs; T1, 1000 Gs; T2, 2000 Gs; T3, 3000 Gs; T4, 4000 Gs; T5, 5000 Gs) affect the degradation rate of biodegradable film, soil watersalt distribution, growth, and quality of processing tomatoes. The traditional PE film mulching and non-magnetized irrigation were used as the control group (MPET0). The results demonstrated that magnetized water irrigation slowed down the degradation rate of biodegradable film. In addition, the magnetized irrigation water can redistributed the soil water-salt patterns under the biodegradable film, improving the soil water content and salt leaching efficiency, with better results in M1 than in M2. Moreover, magnetized water irrigation promoted the growth of tomato leaf area under the biodegradable film, enhancing photochemical efficiency and potential activity of PSII, thereby improving fruit yield, quality, and water use efficiency of tomato. Principal component analysis showed that the comprehensive score of M1T3 treatment was the highest throughout the three years. Furthermore, M1T3 treatment has the highest processing tomato economic benefits during 2021–2023 (24634986 CNY hm2 more than MPET0). Therefore, the use of 3000 Gs magnetized irrigation water combined with black biodegradable film is conducive to improving soil water and salt conditions, reducing residual film pollution, and improving the yield and quality of processing tomatoes, thus ensuring the sustainable development of oasis agriculture.

Water resources, energy, and food are fundamental resources for high-quality regional development. In the process of rapid regional economic growth, integrating the utilization of these fundamental resources has become a critical challenge for achieving high-quality development in the Ili River Valley. To explore the coordinated development status of water, energy, and food (W-E-F) in the Ili River Valley, we constructed a comprehensive evaluation indicator system for the regional W-E-F system, and we calculated and analyzed the comprehensive development level, coupling coordination degree, and spatial equilibrium of the W-E-F system from 2008 to 2020. The results indicate that the comprehensive evaluation indicators of the W-E-F system in the Ili River Valley exhibited an overall upward trend, indicating that the system is moving in a positive direction. Among them, the water subsystem’s comprehensive evaluation indicator showed an upward trend but fluctuated significantly during the study period, with the excessive proportion of agricultural water consumption being a key factor affecting its development. Furthermore, the comprehensive evaluation indicator of the energy subsystem showed a slight downward trend, indicating constraints on the development of energy subsystems. Agricultural surface pollution and industrial waste pollution are the primary factors limiting its development. Meanwhile, due to the significant attention from governments at all levels, the food subsystem has been developed rapidly, with its comprehensive evaluation indicator showing a significant upward trend, which shows that the region is actively promoting food production capacity enhancement initiatives. Additionally, the coupling degree of the W-E-F system remained in a state of coordinated coupling, with an average value between 0.7 and 1.0, indicating a high overall development level, and that the development of each resource affects and constrains that of the other two. The coupling coordination degree transitioned through phases of near coordination, primary coordination, good coordination, and moderate coordination, and all counties and cities showed a tendency to evolve towards high coupling, indicating significant potential for the further development of the regional W-E-F system coupling and coordination. Among the subsystems, the food subsystem exhibited the highest spatial equilibrium (0.78) and the smallest spatial disparities, while the energy subsystem demonstrated the lowest spatial equilibrium (0.40) and the largest spatial disparities. There were still significant issues with the utilization and equilibrium of the regional resource allocation, necessitating integrated planning for the coordinated development of the W-E-F system to achieve sustainable resource management and high-quality ecological and economic development.

Aiming at the problem of a large number of small dense objects in high-altitude shooting and complex background noise interference in the captured scenes, an improved object detection algorithm for YOLOv5 UAV capture scenes is proposed. A Feature Enhancement Block (FEBlock) is first proposed to generate adaptive weights for different receptive field features by convolution, assigning major weights to shallow feature maps to improve small object feature extraction ability. The FEBlock is then integrated into Spatial Pyramid Pooling (SPP) to generate Enhanced Spatial Pyramid Pooling (ESPP), which performs feature enhancement for the result of each maximum pooling; and creates new features containing multi-scale contextual information with better feature characterization capability by weighting fused contextual features. Secondly, the Self-Characteristic Expansion Plate (SCEP) is proposed, which achieves the fusion and expansion of feature information through compression, non-linear mapping, and expansion with its own module, further improving the network’s capacity for feature extraction and generating a new spatial pyramid pooling (ESPP-S) by splicing with ESPP. Finally, a shallower feature map is added as a detection layer to the YOLOv5 network model’s large, medium, and small detection layers to improve the network’s detection performance for medium and long-range objects. Experiments were conducted on the VisDrone2021 dataset, and the results showed that the improved YOLOv5 model improved mAP0.5 by 4.6%, mAP0.5:0.95 by 2.9%, and precision by 2.7%. The mAP0.5 of the model trained at the input resolution of $1024\times1024$ reached 56.8%. The experiments show that the improved YOLOv5 model can improve object detection accuracy for UAV capture scenes.

Abstract Doping of foreign atoms and construction of unique structures are considered as effective approaches to design high‐activity and strong‐durability electrocatalysts. Herein, we report Fe‐doped nickel hydroxide carbonate hierarchical microtubes with Ag nanoparticles (denoted Ag/NiFeHC HMTs) through hydrolysis precipitation process. Experimental tests and density functional theory calculations reveal that Fe doping can tune the electron configuration to enhance the conductivity, markedly improve the electrochemical surface area to expose more active sites, and act as reactive centers to lower the free energy of the rate determination step. In addition, the unique hierarchical structure can also offer active sites and excellent cycling stability. Benefitting from these advantages, the as‐obtained Ag/NiFeHC HMTs show excellent oxygen evolution reaction activity, with an overpotential of 208 mV at 10 mA cm−2 in 1.0 M KOH. Also, it could achieve long‐term stability at a current density of 20 mA cm−2 for 24 h.

Abstract COVID-19 has inflicted the world for over two years. The recent mutant virus strains pose greater challenges to disease prevention and treatment. COVID-19 can cause acute respiratory distress syndrome (ARDS) and extrapulmonary injury. Dynamic monitoring of each patient's condition is necessary to timely tailor treatments, improve prognosis and reduce mortality. Point-of-care ultrasound (POCUS) is broadly used in patients with ARDS. POCUS is recommended to be performed regularly in COVID-19 patients for respiratory failure management. In this review, we summarized the ultrasound characteristics of COVID-19 patients, mainly focusing on lung ultrasound and echocardiography. Furthermore, we also provided the experience of using POCUS to manage COVID-19-related ARDS.

A new parameter estimation method for a UAV braking system with unknown friction parameters is suggested. The unknown part containing friction is separated from the coupling system. The law of parameter updating is driven by the estimation error extracted by the auxiliary filter. A controller is developed to guarantee the convergence of the parameter estimation and tracking errors simultaneously. Furthermore, a designed performance index function enables the system to track the desired slip rate optimally. The optimal value of the performance function is updated by a single critic neural network (NN) to obtain comprehensive optimization of the control energy consumption, dynamic tracking error, and filtering error during braking. In addition, the unknown bounded interference and neural network approximation errors are compensated by robust integral terms. Simulation results are presented to confirm the effectiveness of the proposed control scheme.

Background. The cholinergic anti-inflammatory pathway connects the immune response system and the nervous system via the vagus nerve. The key regulatory receptor is the α7-subtype of the nicotinic acetylcholine receptor (α7nAChR). Cholinergic anti-inflammatory pathway has been proved to be effective in suppressing the inflammation responses in acute lung injury (ALI). Dendritic cells (DCs), the important antigen-presenting cells, also express the α7nAChR. Past studies have indicated that reducing the quantity of mature conventional DCs and inhibiting the maturation of pulmonary DCs may prove effective for the treatment of ALI. However, the effects of cholinergic anti-inflammatory pathway on maturation, function, and quantity of DCs and conventional DCs in ALI remain unclear. Objective. It was hypothesized that cholinergic anti-inflammatory pathway may inhibit the inflammatory response of ALI by regulating maturation, phenotype, and quantity of DCs and conventional DCs. Methods. GTS-21 (GTS-21 dihydrochloride), an α7nAchR agonist, was prophylactically administered in sepsis-induced ALI mouse model and LPS-primed bone marrow-derived dendritic cells. The effects of GTS-21 were observed with respect to maturation, phenotype, and quantity of DCs, conventional DCs, and conventional DCs2 (type 2 conventional DCs) and the release of DC-related proinflammatory cytokines in vivo and in vitro. Results. The results of the present study revealed that GTS-21 treatment decreased the maturation of DCs and the production of DC-related proinflammatory cytokines in vitro and in sepsis-induced ALI mouse model; it reduced the quantity of CD11c+MHCII+ conventional DCs and CD11c+CD11b+ conventional DCs2 in vivo experiment. Conclusions. Cholinergic anti-inflammatory pathway contributes to the reduction in the inflammatory response in ALI by regulating maturation, phenotype, and quantity of DCs, conventional DCs, and conventional DCs2.

In mining industries, the backfill becomes more and more important due to the environment protection concern. But most backfill investigations focus on the underground model and backfill materials. In this research, the paste backfill process based on the process control is investigated and a new paste backfill process model is proposed according to the Torricelli's law and Bernoulli principle. In order to deal with the unknown nonlinear function of the proposed backfill model, a Petri net(PN) structure is presented and a new Petri net neural network(PNNN) is introduced to approximate the unknown nonlinear function. Then, a robust controller is designed for the backfill process with PNNN and the closed loop stability is guaranteed by Lyapunov function candidate. The effectiveness of the proposed model with new PNNN and the robust controller are verified by simulation results.

This paper proposes a modified adaptive neural control algorithm with a funnel function for nonlinear two-inertia servomechanisms with backlash and external disturbance. A continuous tracking differentiator is employed to replace the first-order filter in the traditional dynamic surface control design. A novel funnel function is employed and used in control design to improve the control performance. Then, an adaptive neural dynamic surface controller based on funnel control is presented to guarantee the tracking performance of two-inertia servomechanisms. In addition, the unknown dynamics, including backlash, nonlinear friction, and external disturbance, are approximated by using the echo state neural network and compensated online. The comparative experimental results validate the effectiveness of the developed control algorithm based on a two-inertia servo mechanism.

The shuttle effect hinders the practical application of lithium-sulfur (Li-S) batteries due to the poor affinity between a substrate and Li polysulfides (LiPSs) and the sluggish transition of soluble LiPSs to insoluble Li2S or elemental S. Here, we report that Ni hexatomic clusters embedded in a nitrogen-doped three-dimensional (3D) graphene framework (Ni-N/G) possess stronger interaction with soluble polysulfides than that with insoluble polysulfides. The synthetic electrocatalyst deployed in the sulfur cathode plays a multifunctional role: (i) selectively adsorbing the polysulfides dissolved in the electrolyte, (ii) expediting the sluggish liquid-solid phase transformations at the active sites as electrocatalysts, and (iii) accelerating the kinetics of the electrochemical reaction of multielectron sulfur, thereby inhibiting the dissolution of LiPSs. The constructed S@Ni-N/G cathode delivers an areal capacity of 9.43 mAh cm-2 at 0.1 C at S loading of 6.8 mg cm-2, and it exhibits a gravimetric capacity of 1104 mAh g-1 with a capacity fading rate of 0.045% per cycle over 50 cycles at 0.2 C at S loading of 2.0 mg cm-2. This work opens a rational approach to achieve the selective adsorption and expediting of polysulfide transition for the performance enhancement of Li-S batteries.

A new neural network sliding mode control (NNSMC) is proposed for backlash-like hysteresis nonlinear system in this paper. Firstly, only one neural network is designed to estimate the unknown system states and hysteresis section instead of multiscale neural network at former researches since that can save computation and simplify the controller design. Secondly, a new NNSMC is proposed for the hysteresis nonlinearity where it does not need tracking error transformation. Finally, the Lyapunov functions are adopted to guarantee the stabilities of the identification and control strategies semiglobally uniformly ultimately bounded (UUB). Two cases simulations are proved the effectiveness of the presented identification approach and the performance of the NNSMC.

An adaptive high-order neural network (HONN) control strategy is proposed for a hysteresis motor driving servo system with the Bouc-Wen model. To simplify control design, the model is rewritten as a canonical state space form firstly through coordinate transformation. Then, a high-gain state observer (HGSO) is proposed to estimate the unknown transformed state. Afterward, a filter for the tracking errors is adopted which converts the vector error e into a scalar error s. Finally, an adaptive HONN controller is presented, and a Lyapunov function candidate guarantees that all the closed-loop signals are uniformly ultimately bounded (UUB). Simulations verified the effectiveness of the proposed neural network adaptive control strategy for the hysteresis servo motor system.

An adaptive control based on a new Multiscale Chebyshev Neural Network (MSCNN) identification is proposed for the backlash-like hysteresis nonlinearity system in this paper. Firstly, a MSCNN is introduced to approximate the backlash-like nonlinearity of the system, and then, the Lyapunov theorem assures the identification approach is effective. Afterward, to simplify the control design, tracking error is transformed into a scalar error with Laplace transformation. Therefore, an adaptive control strategy based on the transformed scalar error is proposed, and all the signals of the closed-loop system are uniformly ultimately bounded (UUB). Finally, simulation results have demonstrated the performance of the proposed control scheme.

This paper proposes an adaptive barrier controller for servomechanisms with friction compensation. A modified LuGre model is used to capture friction dynamics of servomechanisms. This model is incorporated into an augmented neural network (NN) to account for the unknown nonlinearities. Moreover, a barrier Lyapunov function (BLF) is utilized to each step in a backstepping design procedure. Then, a novel adaptive control method is well suggested to ensure that the full-state constraints are within the given boundary. The stability of the closed-loop control system is proved using Lyapunov stability theory. Comparative experiments on a turntable servomechanism confirm the effectiveness of the devised control method.

A method for the rapid determination of 4-hexylresorcinol (4-HR) residue in shrimp by solid phase extraction (SPE) ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was established. 4-HR was extracted twice with methanol, and the extract was formulated into methanol-water solution (1:1). After being cleaned up and concentrated by a PRIME HLB solid phase extraction column, the sample was analyzed by UPLC-MS/MS and quantitatively determined by an external standard method. The separation was performed with a gradient system consisting of water and acetonitrile as the mobile phase. Monitoring was performed by electrospray ionization (ESI) in negative ion mode using multiple ion reaction monitoring (MRM). Good linearity was obtained in the concentration range of 1.0–100.0 μg/L, with correlation coefficients larger than 0.999. The limit of detection (LOD) was 0.25 μg/kg and the limit of quantification (LOQ) was 0.80 μg/kg. The average recoveries of 4-HR at spiked concentrations of 2.40, 6.40 and 16 μg/kg ranged from 81.35% to 94.68% with the relative standard deviations (n = 6) from 3.57% to 6.86%. The results showed that the method is simple, fast, sensitive, reliable, and reproducible; thus, it could be used as a rapid confirmation and quantitative analysis method of 4-HR residue in aquatic products.