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Unmanned aerial vehicle (UAV) formations for bearing-only passive detection are increasingly important in modern military confrontations, and the array of the formation is one of the decisive factors affecting the detection accuracy of the system. How to plan the optimal geometric array in bearing-only detection is a complex nondeterministic polynomial problem, and this paper proposed the distributed stochastic subgradient projection algorithm (DSSPA) with layered constraints to solve this challenge. Firstly, based on the constraints of safe flight altitude and fixed baseline, the UAV formation is layered, and the system model for bearing-only cooperative localisation is constructed and analysed. Then, the calculation formula for geometric dilution of precision (GDOP) in the observation plane is provided, this nonlinear objective function is appropriately simplified to obtain its quadratic form, ensuring that it can be adapted and used efficiently in the system model. Finally, the proposed distributed stochastic subgradient projection algorithm (DSSPA) combines the idea of stochastic gradient descent with the projection method. By performing a projection operation on each feasible solution, it ensures that the updated parameters can satisfy the constraints while efficiently solving the convex optimisation problem of array planning. In addition to theoretical proof, this paper also conducts three simulation experiments of different scales, validating the effectiveness and superiority of the proposed method for bearing-only detection array planning in UAV formations. This research provides essential guidance and technical reference for the deployment of UAV formations and path planning of detection platforms.
Asymptotic expansions of the maximum likelihood estimator (MLE) and weighted likelihood estimator (WLE) of an examinee’s ability are derived while item parameter estimators are treated as covariates measured with error. The asymptotic formulae present the amount of bias of the ability estimators due to the uncertainty of item parameter estimators. A numerical example is presented to illustrate how to apply the formulae to evaluate the impact of uncertainty about item parameters on ability estimation and the appropriateness of estimating ability using the regular MLE or WLE method.
Let $[a_1(x),a_2(x),\ldots ,a_n(x),\ldots ]$ be the continued fraction expansion of $x\in [0,1)$ and $q_n(x)$ be the denominator of its nth convergent. The irrationality exponent and Khintchine exponent of x are respectively defined by
We study the multifractal spectrum of the irrationality exponent and the Khintchine exponent for continued fractions with nondecreasing partial quotients. For any $v>2$, we completely determine the Hausdorff dimensions of the sets $\{x\in [0,1): a_1(x)\leq a_2(x)\leq \cdots , \overline {v}(x)=v\}$ and
This study aimed to investigate the effects of esketamine (Esk) combined with dexmedetomidine (Dex) on postoperative delirium (POD) and quality of recovery (QoR) in elderly patients undergoing thoracoscopic radical lung cancer surgery.
Methods
In this prospective, randomized, and controlled study, 172 elderly patients undergoing thoracoscopic radical lung cancer surgery were divided into two groups: the Esk + Dex group (n = 86) and the Dex group a (n = 86). The primary outcome was the incidence of POD within 7 days after surgery and the overall Quality of Recovery−15 (QoR − 15) scores within 3 days after surgery. Secondary outcomes included postoperative adverse reactions, extubation time, PACU stay, and hospitalization time. Serum levels of IL-6, IL-10, S100β protein, NSE, CD3+, CD4+, and CD8+ were detected from T0 to T5.
Results
Compared with the Dex group, the incidence of POD in the Esk + Dex group was significantly lower at 7 days after surgery (14.6% vs 30.9%; P = 0.013). The QoR − 15 score was significantly increased 3 days after surgery (P < 0.01). Levels of IL-6 and CD8+ were significantly decreased, and IL − 10 levels were significantly increased at T1-T2 (P < 0.05). At T1-T4, NSE levels were significantly decreased, while CD3+ and CD4+/CD8+ values were significantly increased (P < 0.01). At T1-T5, serum S100β protein concentration decreased significantly, and CD4+ value increased significantly (P < 0.01). The incidence of nausea/vomiting and hyperalgesia decreased significantly 48 hours after surgery (P < 0.01). The duration of extubation, PACU stay, and postoperative hospitalization were significantly shortened.
Conclusions
Esketamine combined with dexmedetomidine can significantly reduce the POD incidence and improve the QoR in patients undergoing thoracoscopic radical lung cancer surgery, which may be related to the improvement of cellular immune function.
The material removal rate (MRR) serves as a crucial indicator in the chemical mechanical polishing (CMP) process of semiconductor wafers. Currently, the mainstream method to ascertain the MRR through offline measurements proves time inefficient and struggles to represent process variability accurately. An efficient MRR prediction model based on stacking ensemble learning that integrates models with disparate architectures was proposed in this study. First, the processing signals collected during wafer polishing, as available in the PHM2016 dataset, were analyzed and preprocessed to extract statistical and neighbor domain features. Subsequently, Pearson correlation coefficient analysis (PCCA) and principal component analysis (PCA) were employed to fuse the extracted features. Ultimately, random forest (RF), light gradient boosting machine (LightGBM), and backpropagation neural network (BPNN) with hyperparameters optimized by the Bayesian Optimization Algorithm were integrated to establish an MRR prediction model based on stacking ensemble learning. The developed model was verified on the PHM2016 benchmark test set, and a Mean Square Error (MSE) of 7.72 and a coefficient of determination (R2) of 95.82% were achieved. This indicates that the stacking ensemble learning based model, integrated with base models of disparate architectures, offers considerable potential for real-time MRR prediction in the CMP process of semiconductor wafers.
The tension distribution problem of cable-driven parallel robots is inevitable in real-time control. Currently, iterative algorithms or geometric algorithms are commonly used to solve this problem. Iterative algorithms are difficult to improve in real-time performance, and the tension obtained by geometric algorithms may not be continuous. In this paper, a novel tension distribution method for four-cable, 3-DOF cable-driven parallel robots is proposed based on the wave equation. The tension calculated by this method is continuous and differentiable, without the need for iterative computation or geometric centroid calculations, thus exhibiting good real-time performance. Furthermore, the feasibility and rationality of this algorithm are theoretically proven. Finally, the real-time performance and continuity of cable tension are analyzed through a specific numerical example.
High-elevation environments present harsh challenges for the pursuit of agropastoral subsistence strategies and relatively little is known about the mechanisms early communities employed to adapt to such locations successfully. This article presents the sequential carbon and oxygen analysis of archaeological caprine teeth from Bangga (c. 3000–2200 BP), which is approximately 3750masl on the Tibetan Plateau. Made visible through this method, intra-tooth variation in isotopic composition allows insights into herding strategies that possibly included the provisioning of livestock with groundwater and agricultural fodder and summer grazing in saline or marsh environments. Such intensive provisioning differs markedly from lower-elevation agropastoralism.
Autonomous exploration in unknown environments has become a critical capability of mobile robots. Many methods often suffer from problems such as exploration goal selection based solely on information gain and inefficient tour optimization. Recent reinforcement learning-based methods do not consider full area coverage and the performance of transferring learned policy to new environments cannot be guaranteed. To address these issues, a dual-stage exploration method has been proposed, which combines spatial clustering of possible exploration goals and Traveling Salesman Problem (TSP) based tour planning on both local and global scales, aiming for efficient full-area exploration in highly convoluted environments. Our method involves two stages: exploration and relocation. During the exploration stage, we introduce to generate local navigation goal candidates straight from clusters of all possible local exploration goals. The local navigation goal is determined through tour planning, utilizing the TSP framework. Moreover, during the relocation stage, we suggest clustering all possible global exploration goals and applying TSP-based tour planning to efficiently direct the robot toward previously detected but yet-to-be-explored areas. The proposed method is validated in various challenging simulated and real-world environments. Experimental results demonstrate its effectiveness and efficiency. Videos and code are available at https://github.com/JiatongBao/exploration.
This study investigates the impact of molecular thermal fluctuations on compressible decaying isotropic turbulence using the unified stochastic particle (USP) method, encompassing both two-dimensional (2-D) and three-dimensional (3-D) scenarios. The findings reveal that the turbulent spectra of velocity and thermodynamic variables follow the wavenumber (k) scaling law of ${k}^{(d-1)}$ for different spatial dimensions $d$ within the high wavenumber range, indicating the impact of thermal fluctuations on small-scale turbulent statistics. With the application of Helmholtz decomposition, it is found that the thermal fluctuation spectra of solenoidal and compressible velocity components (${\boldsymbol {u}}_{s}$ and ${\boldsymbol {u}}_{c}$) follow an energy ratio of 1 : 1 for 2-D cases, while the ratio changes to 2 : 1 for 3-D cases. Comparisons between 3-D turbulent spectra obtained through USP simulations and direct numerical simulations of the Navier–Stokes equations demonstrate that thermal fluctuations dominate the spectra at length scales comparable to the Kolmogorov length scale. Additionally, the effect of thermal fluctuations on the spectrum of ${\boldsymbol {u}}_{c}$ is significantly influenced by variations in the turbulent Mach number. We further study the impact of thermal fluctuations on the predictability of turbulence. With initial differences caused by thermal fluctuations, different flow realizations display significant disparities in velocity and thermodynamic fields at larger scales after a certain period of time, which can be characterized by ‘inverse error cascades’. Moreover, the results suggest a strong correlation between the predictabilities of thermodynamic fields and the predictability of ${\boldsymbol {u}}_{c}$.
Various psychosocial and psychological interventions have been developed to reduce schizophrenia relapse prevention. A better understanding of these active interventions is important for clinical practice and for meaningful allocation of resources. However, no bibliometric analysis of this area has been conducted. Studies were retrieved from the Web of Science Core Collection database. The publication outputs and cooperation of institutions were visualized with Origin 2021. Global cooperation was visualized using ArcGIS Pro3.0. VOSviewer was used to generate visualizations of network of authors and keywords. The number of annual publications generally showed a fluctuating upward trend over the past 20 years. Germany published the most relevant articles (361, 26.76%). The Technical University of Munich was the most productive institution (70, 9.86%). Leucht Stefan published the most articles (46, 6.48%) and had the highest number of citations (4,375 citations). Schizophrenia Research published the most studies (39, 5.49%). Keywords were roughly classified into three clusters: cognitive behavioral therapy (CBT), family interventions and family psychoeducation and other factors related to interventions. The findings provided the current status of research on psychosocial and psychological interventions for schizophrenia relapse prevention from a bibliometric perspective. Recent research has mainly focused on CBT, family interventions and family psychoeducation.
This study aimed to evaluate the methodological quality of existing meta-analyses (MA) and the quality of evidence for outcome indicators to provide an updated overview of the evidence concerning the therapeutic efficacy of the Mediterranean diet (MD) for various types of CVD.
Design:
We conducted comprehensive searches of PubMed, Cochrane Library, and Embase databases. The quality of the MA was assessed using the A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2) checklist, while the Grading of Recommendations Assessment, Development and Evaluation (GRADE) evidence evaluation system was employed to evaluate the quality of evidence for significant outcomes.
Setting:
The CVD remains a significant contributor to global mortality. Multiple MA have consistently demonstrated the efficacy of medical interventions in managing CVD. However, due to variations in the scope, quality and outcomes of these reviews, definitive conclusions are yet to be established.
Participants:
This study included five randomized trials and twelve non-randomized studies, with a combined participant population of 716 318.
Results:
The AMSTAR 2 checklist revealed that 54·55 % of the studies demonstrated high quality, while 9·09 % exhibited low quality, and 36·36 % were deemed critically low quality. Additionally, there was moderate evidence supporting a positive correlation between MD and CHD/acute myocardial infarction, stroke, heart failure, cardiovascular events, coronary events and major adverse cardiovascular events.
Conclusions:
This study indicates that although recognizing the potential efficacy of MD in managing CVD, the quality of the methodology and the evidence for the outcome indicators remain unsatisfactory.
Soft drink consumption has become a highly controversial public health issue. Given the pattern of consumption in China, sugar-sweetened beverage is the main type of soft drink consumed. Due to containing high levels of fructose, a soft drink may have a deleterious effect on handgrip strength (HGS) due to oxidative stress, inflammation and insulin resistance. However, few studies show an association between soft drink consumption and HGS in adults. We aimed to investigate the association between soft drink consumption and longitudinal changes in HGS among a Chinese adult population. A longitudinal population-based cohort study (5-year follow-up, median: 3·66 years) was conducted in Tianjin, China. A total of 11 125 participants (56·7 % men) were enrolled. HGS was measured using a handheld digital dynamometer. Soft drink consumption (mainly sugar-containing carbonated beverages) was measured at baseline using a validated FFQ. ANCOVA was used to evaluate the association between soft drink consumption and annual change in HGS or weight-adjusted HGS. After adjusting for multiple confounding factors, the least square means (95 % CI) of annual change in HGS across soft drink consumption frequencies were −0·70 (–2·49, 1·09) for rarely drinks, −0·82 (–2·62, 0·97) for < 1 cup/week and −0·86 (–2·66, 0·93) for ≥ 1 cup/week (Pfor trend < 0·05). Likewise, a similar association was observed between soft drink consumption and annual change in weight-adjusted HGS. The results indicate that higher soft drink consumption was associated with faster HGS decline in Chinese adults.
This paper extends the work of Tamano & Morinishi (J. Fluid Mech., vol. 548, 2006, pp. 361–373) by simulating supersonic turbulent channel flow with asymmetric thermal walls using a larger computational domain and a finer mesh. Direct numerical simulation is carried out for four cases with different thermal wall boundaries at the top wall at fixed $Ma=1.5$, $Re=6000$ and $Pr=0.72$, while the bottom wall is maintained at a constant temperature of $T_L$ equal to the reference temperature. These cases are referred to as the adiabatic case TAd, where the top wall is adiabatic; the pseudo-adiabatic case T32, where the top wall is isothermal with temperature $T_{w,t}=T_A$; the sub-adiabatic case T25, with $T_{w,t}=0.77T_A$; and the super-adiabatic case T40, with $T_{w,t}=1.24T_A$. Here, $T_A=3.234$ is the mean temperature at the adiabatic wall in the TAd case. The objective of this study is to compare and contrast the TAd case with its corresponding T32 case, and to investigate the effect of the wall temperature difference between the two isothermal walls. Comparisons of the basic turbulent statistics, the heat transfer between the Favre-averaged mean-flow kinetic energy, the Favre-averaged turbulent kinetic energy and the Favre-averaged mean internal energy, as well as the wall heat transfer properties, indicate that the TAd case and its corresponding T32 case are generally equivalent. The only discernible difference is in the region very close to the top wall for the temperature-fluctuation-related quantities. The analysis reveals that the asymmetry of the thermal walls causes asymmetry in the flow and thermal fields. In addition, the transfer of the heat generated by the pressure dilatation and the viscous stress is facilitated by the turbulent heat flux term and the mean molecular heat flux term.
To meet the demands of laser-ion acceleration at a high repetition rate, we have developed a comprehensive diagnostic system for real-time and in situ monitoring of liquid sheet targets (LSTs). The spatially resolved rapid characterizations of an LST’s thickness, flatness, tilt angle and position are fulfilled by different subsystems with high accuracy. With the help of the diagnostic system, we reveal the dependence of thickness distribution on collision parameters and report the 238-nm liquid sheet generated by the collision of two liquid jets. Control methods for the flatness and tilt angle of LSTs have also been provided, which are essential for applications of laser-driven ion acceleration and others.
Robots with multi-sensors always have a problem of weak pairing among different modals of the collected information produced by multi-sensors, which leads to a bad perception performance during robot interaction. To solve this problem, this paper proposes a Force Vision Sight (FVSight) sensor, which utilizes a distributed flexible tactile sensing array integrated with a vision unit. This innovative approach aims to enhance the overall perceptual capabilities for object recognition. The core idea is using one perceptual layer to trigger both tactile images and force-tactile arrays. It allows the two heterogeneous tactile modal information to be consistent in the temporal and spatial dimensions, thus solving the problem of weak pairing between visual and tactile data. Two experiments are specially designed, namely object classification and slip detection. A dataset containing 27 objects with deep presses and shallow presses is collected for classification, and then 20 slip experiments on three objects are conducted. The determination of slip and stationary state is accurately obtained by covariance operation on the tactile data. The experimental results show the reliability of generated multimodal data and the effectiveness of our proposed FVSight sensor.
We construct an autoregressive moving average (ARMA) model consisting of the history and random effects for the streamwise velocity fluctuation in boundary-layer turbulence. The distance to the wall and the boundary-layer thickness determine the time step and the order of the ARMA model, respectively. Based on the autocorrelation's analytical expression of the ARMA model, we obtain a global analytical expression for the second-order structure function, which asymptotically captures the inertial, dynamic and large-scale ranges. Specifically, the exponential autocorrelation of the ARMA model arises from the autoregressive coefficients and is modified to logarithmic behaviour by the moving-average coefficients. The asymptotic expressions enable us to determine model coefficients by existing parameters, such as the Kolmogorov and the Townsend–Perry constants. A consequent double-log expression for the characteristic length scale is derived and is justified by direct numerical simulation data with $Re_\tau \approx 5200$ and field-measured neutral atmospheric surface layer data with $Re_\tau \sim O(10^6)$ from the Qingtu Lake Observation Array site. This relation is robust because it applies to $Re_\tau$ from $O(10^4)$ to $O(10^6)$, and even when the statistics of natural ASL deviate from those of canonical boundary-layer turbulence, e.g. in the case of imbalance in energy production and dissipation, and when the Townsend–Perry constant deviates from traditional values.
Foilless diode are widely used in high-power microwave devices, but the traditional foilless diodes have large volume, heavy weight, and high power consumption, which are not conducive to the application of high-power microwave system on mobile platform. In order to reduce the size of the foilless diode, improve the transmission efficiency of electron beams, and reduce the weight and power consumption of the guiding magnetic field system, an axial foilless diode with a composite guiding magnetic field system is developed in this paper. By adjusting the structure size and magnetic field parameters of solenoid coil, permanent magnet, and soft magnet, the configuration of the composite magnetic field is optimized. The diameter of the anode tube is about 40% smaller than that of the original structure, and the weight and power consumption of the guiding magnetic system are about 40% lower than that of the original system when the same axial magnetic field intensity in the uniform region is generated. When the magnetic field strength of the permanent magnet is set as 1.4 T and that of the solenoid coil is in the range of 0.5 T∼1 T, the electron beam transmission efficiency is 100%, and the diode impedance is adjustable in the range of 100 Ω∼240 Ω. The experimental results verify the correctness of the simulation analysis. The experimental results show that when the magnetic field strength of the solenoid coil is 0.98 T (0.5 T) and that of the permanent magnet is 1.4 T, the transmission efficiency of the high-current annular electron beam with a peak voltage of 636 kV (590 kV) and a peak current of 3.3 kA (2.6 kA) is 100%, and the diode impedance is about 194 Ω (220 Ω).
Fused silica is an optical material with excellent performance, and it is widely used in the fabrication of optics in various high-power laser systems. With the gradual improvement of laser systems, the quality of optics becomes crucial. Taking magnetorheological finishing (MRF), ion beam sputtering etching (IBSE), and advanced mitigation processing (AMP) as the means, this work focuses on exploring the damage characteristics evolution of fused silica under different techniques. In this work, IBSE technique was used to determinedly polish the optical surface after removing damage layer by MRF technique, and AMP technique was applied to etch the surface with a certain depth. Then, 10 J/cm2 (355 nm, 5 ns) laser was used to irradiate the optical surface, and the damage density of optics maintained at a low level, about 0.001/mm2, which proves that MRF, IBSE, and AMP techniques can effectively improve the laser damage resistance of optics.
Schistosomiasis, a parasite infectious disease caused by Schistosoma japonicum, often leads to egg granuloma and fibrosis due to the inflammatory reaction triggered by egg antigens released in the host liver. This study focuses on the role of the egg antigens CP1412 protein of S. japonicum (SjCP1412) with RNase activity in promoting liver fibrosis. In this study, the recombinant egg ribonuclease SjCP1412, which had RNase activity, was successfully prepared. By analysing the serum of the population, it has been proven that the anti-SjCP1412 IgG in the serum of patients with advanced schistosomiasis was moderately correlated with liver fibrosis, and SjCP1412 may be an important antigen associated with liver fibrosis in schistosomiasis. In vitro, the rSjCP1412 protein induced the human liver cancer cell line Hep G2 and liver sinusoidal endothelial cells apoptosis and necrosis and the release of proinflammatory damage-associated molecular patterns (DAMPs). In mice infected with schistosomes, rSjCP1412 immunization or antibody neutralization of SjCP1412 activity significantly reduced cell apoptosis and necroptosis in liver tissue, thereby reducing inflammation and liver fibrosis. In summary, the SjCP1412 protein plays a crucial role in promoting liver fibrosis during schistosomiasis through mediating the liver cells apoptosis and necroptosis to release DAMPs inducing an inflammatory reaction. Blocking SjCP1412 activity could inhibit its proapoptotic and necrotic effects and alleviate hepatic fibrosis. These findings suggest that SjCP1412 may be served as a promising drug target for managing liver fibrosis in schistosomiasis japonica.