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Abstract The use of unmanned aerial vehicle (UAV) technology to inspect extensive peach orchards to improve fruit yield and quality is currently a major area of research. The challenge is to accurately detect peach diseases in real time, which is critical to improving peach production. The dense arrangement of peaches and the uneven lighting conditions significantly hamper the accuracy of disease detection. To overcome this, this paper presents a dual-channel transformer network (DCTNet) for peach disease detection. First, an Adaptive Dual-Channel Affine Transformer (ADCT) is developed to efficiently capture key information in images of diseased peaches by integrating features across spatial and channel dimensions within blocks. Next, a Robust Gated Feed Forward Network (RGFN) is constructed to extend the receptive field of the model by improving its context aggregation capabilities. Finally, a Local–Global Network is proposed to fully capture the multi-scale features of peach disease images through a collaborative training approach with input images. Furthermore, a peach disease dataset including different growth stages of peaches is constructed to evaluate the detection performance of the proposed method. Extensive experimental results show that our model outperforms other sophisticated models, achieving an $${AP}_{50}$$ AP 50 of 95.57% and an F1 score of 0.91. The integration of this method into UAV systems for surveying large peach orchards ensures accurate disease detection, thereby safeguarding peach production.

Weapon target assignment (WTA) is a typical problem in the command and control of modern warfare. Despite the significance of the problem, traditional algorithms still have shortcomings in terms of efficiency, solution quality, and generalization. This paper presents a novel multi-objective evolutionary optimization algorithm (MOEA) that integrates a deep Q-network (DQN)-based adaptive mutation operator and a greedy-based crossover operator, designed to enhance the solution quality for the multi-objective WTA (MO-WTA). Our approach (NSGA-DRL) evolves NSGA-II by embedding these operators to strike a balance between exploration and exploitation. The DQN-based adaptive mutation operator is developed for predicting high-quality solutions, thereby improving the exploration process and maintaining diversity within the population. In parallel, the greedy-based crossover operator employs domain knowledge to minimize ineffective searches, focusing on exploitation and expediting convergence. Ablation studies revealed that our proposed operators significantly boost the algorithm performance. In particular, the DQN mutation operator shows its predictive effectiveness in identifying candidate solutions. The proposed NSGA-DRL outperforms state-and-art MOEAs in solving MO-WTA problems by generating high-quality solutions.

AbstractTo prevent water inrush hazards of mining under the Quaternary unconsolidated confined aquifer in North China coalfield, it is necessary to build a water inrush prediction model to guarantee coal safety production. The current method of evaluating mining hazards under unconsolidated confined aquifers is easy to fall into the problems of simple superposition of evaluation factors, large subjectivity of the factor selection, and low accuracy of prediction results. In this paper, an analytic hierarchy process (AHP) is improved according to contribution of information value method (IVM) to analyze the impact of water inrush factors. The factor weight values are considered in calculating the total information value of IVM to build a coupled AHP-IVM model. The information value of each factor is calculated through IVM, and area under curve (AUC) value is used to rank the factors, to exclude the subjective judgment of the importance of each factor. The geological and hydrogeological data of Qinan coal mine in Huaibei coalfield are analyzed and organized. The results suggest that the coupled AHP-IVM model has an AUC value of 0.8309, indicating its great potential and practical significance for future mining operations.

BackgroundInvasive mold diseases (IMD) is associated with high mortality and a substantial economic burden. For high-risk patients, fever drive or diagnostic drive therapy is usually initiated prior to the differential diagnosis of the pathogen. This study evaluated the cost-effectiveness of isavuconazole, posaconazole, vs. voriconazole in the treatment of IMD from the perspective of the Chinese healthcare system, informing healthcare decision-making and resource allocation.MethodsA decision analytic model was constructed using TreeAge Pro 2011 software to evaluate the cost-effectiveness of the entire disease course. We assumed that the prevalence of mucormycosis in the patients entering the model was 7.8%. Efficacy, cost, adverse events, and other data included in the model were mainly derived from clinical studies, published literature, and publicly available databases. The primary outcomes of the model output were total cost, quality-adjusted life years (QALYs), life years (Lys), and incremental cost-effectiveness ratio (ICER). The willing-to-pay (WTP) threshold was defined as one to three times China's GDP per capita in 2022. One-way sensitivity analysis and probability sensitivity analysis were used to determine the robustness of the model. At the same time, the cost-effectiveness of three triazole antifungal agents under a broader range of mucormycosis prevalence, when voriconazole was covered by medical insurance reimbursement, and after the price reduction of posaconazole was discussed.ResultsCompared with voriconazole, isavuconazole provided an additional 0.38 Lys (9.29 vs. 8.91 LYs) and 0.31 QALYs (7.62 vs. 7.31 QALYs); ICER was $15,702.46/QALY, well-below the WTP threshold ($38,223/QALY). However, posaconazole did not provide a significant economic advantage over voriconazole (9.40 vs. 9.36 Lys; 7.71 vs. 7.68 QALYs; ICER $64,466.57/QALY). One-way sensitivity analysis found that ICER was highly sensitive to the mortality of patients with invasive aspergillus infection. In the probabilistic sensitivity analysis, when the WTP threshold was $38,223/QALY, the probability of isavuconazole being cost-effective was 72.9%. The scenario analysis results indicated that posaconazole would become cost-effective when the price was reduced by 15% or the prevalence of mucormycosis was 14%.ConclusionsIsavuconazole represents a cost-effective initial option for treating IMD in high-risk hematological patients prior to the differential diagnosis of pathogens. It will also be economical when a 15% reduction in posaconazole cost is achieved.

Background: With the increase in drug resistance rates of pathogens isolated from complicated intra-abdominal infections (cIAIs), ceftazidime/avibactam (CAZ-AVI) is increasingly used clinically. However, given the high drug cost and the fact that not yet covered by the health insurance payment, this study evaluated the cost-effectiveness of CAZ-AVI plus metronidazole versus meropenem as a first-line empiric treatment for cIAIs from the perspective of the Chinese healthcare system. Methods: A decision analytic model with a one-year time horizon was constructed to assess the cost-effectiveness based on the entire disease course. Model inputs were mainly obtained from clinical studies, published literature, and publicly available databases. Primary outcomes were cost, quality-adjusted life years (QALYs), life years (Lys), and incremental cost-effectiveness ratio (ICER). One-way sensitivity analysis and probabilistic sensitivity analysis were also performed. Results: In the base cases, compared to meropenem, CAZ-AVI plus metronidazole had a shorter mean hospital length of stay (–0.77 days per patient) and longer life expectancy (+0.05 LYs and +0.06 QALYs). CAZ-AVI plus metronidazole had an ICER of $25517/QALY, which is well below the threshold of $31509 per QALY in China. The one-way sensitivity analysis showed that the change of the treatment duration of CAZ-AVI plus metronidazole was the parameter that most influenced the results of the ICER. In probabilistic sensitivity analysis, CAZ-AVI plus metronidazole was the optimal strategy in 75% of simulations at $31510/QALY threshold. Conclusions: CAZ-AVI plus metronidazole could be considered as a cost-effective option for the empiric treatment of patients with cIAIs in China, and this benefit will be more evident when the price of CAZ-AVI decreases by 23.8%.

This paper investigates a novel multi-objective optimization framework for the multi-stage missile target allocation (M-MTA) problem, which also widely exists in other real-world complex systems. Specifically, a constrained model of M-MTA is built with the trade-off between minimizing the survivability of targets and minimizing the cost consumption of missiles. Moreover, a multi-objective optimization algorithm (NSGA-MTA) is proposed for M-MTA, where the hybrid encoding mechanism establishes the expression of the model and algorithm. Furthermore, rule-based initialization is developed to enhance the quality and searchability of feasible solutions. An efficient non-dominated sorting method is introduced into the framework as an effective search strategy. Besides, the genetic operators with the greedy mechanism and random repair strategy are involved in handling the constraints with maintaining diversity. The results of numerical experiments demonstrate that NSGA-MTA performs better in diversity and convergence than the excellent current algorithms in metrics and Pareto front obtained in 15 scenarios. Taguchi method is also adopted to verify the contribution of proposed strategies, and the results show that these strategies are practical and promotive to performance improvement.

With the characteristics of large space-time and satellite-ground network integration, the space integrated ground network has attracted much attention.Satellites can not only be used as emergency communication supplements, but also serve as air stations to expand the coverage of terrestrial networks, occupying an important position in both military and civilian scenarios.The entity authentication and key negotiation mechanism can prevent the malicious entities from joining the integrated network to steal users’ privacy, and guarantee network information security.In view of the characteristics of the high satellite-ground transmission delays, exposed links, limited processing capability and dynamic topology of the integrated network, a lightweight authentication scheme between satellites and ground suitable for double-layer satellite network was proposed to achieve a secure satellite networking architecture with session keys to protect data transmission.The scheme was based on symmetric cryptographic system, using lightweight cryptographic algorithms and introducing group key and hierarchical management mechanisms.The proposed scheme included three parts: inter-satellite authentication for geostationary earth orbit satellites, layer and inter-satellite authentication for same low earth orbit, and inter-satellite authentication for adjacent low earth orbit satellites.The group key and hierarchical management mechanism improved the efficiency of inter-group information transfer, reduced the authentication pressure on the ground control center, and enhanced the authentication security strength by realizing double verification in the three-entities authentication protocol.Different from the previous single scene authentication, the proposed authentication protocol took the form of multiplexing authentication parameters, which can realize the authentication requirements of dual scenes in one process.The results of Scyther, a protocol formal security simulation tool, show that the proposed scheme achieves secure access authentication.Compared with existing protocols, the proposed scheme improves authentication security and reduces communication and computational overhead.

The TC4 (Ti-6Al-4V) alloy has problems such as low material hardness, poor wear resistance, and abnormal sensitivity to adhesive wear and fretting wear. In this study, we used graphene-reinforced Ti/BN composite coatings prepared on the surface of the TC4 alloy by argon arc cladding technology. We explored the optimal content of graphene to improve its hardness and wear resistance. The physical phases and microstructures of the coatings were analyzed using an X-ray diffractometer, metallurgical microscope, and scanning electron microscope. Microhardness and wear properties of the cladding coating were measured by a Vickers hardness tester and a universal friction and wear tester. The incorporation of graphene resulted in a transformation of the reinforcing phase in the coating from TiN to Ti(N, C). The C element in the molten pool was substituted with the N element in an unending solid solution, resulting in the formation of Ti(N, C) through intermittent nucleation. As the amount of graphene in the molten pool increases, the concentration of carbon (C) also increases. This leads to the continuous growth of Ti(N, C) particles, resulting in a coarser coating structure and a decrease in coating performance. When the graphene content is 5 wt.%, the microstructure refinement of the coating is the most obvious, the microhardness is 900 HV0.2, which is 3 times higher than that of the matrix, and the wear rate is 4.9 × 10−5 mm3/(N·m), which is 4.9 times higher than that of the matrix. The wear mechanism of the coating is primarily abrasive wear with some slight adhesive wear.

As we all know, YOLOv4 can achieve excellent detection performance in object detection and has been effectively applied in many fields. However, the inconsistency of scale features affects the prediction accuracy of the path aggregation network (PANet) in YOLOv4 for small objects, resulting in low detection accuracy. This paper presents YOLOv4, which uses an adaptive recursive path aggregation network (AR-PANet) to improve the detection accuracy of small objects. First, the output characteristics of the PANet are fed back into the backbone network by using a recursive structure to enrich the characteristic information of the object. Second, an adaptive approach is developed to eliminate conflicting information in multi-scale feature space, thereby enhancing scale invariance and promoting feature extraction accuracy for small objects. Finally, the CBAM is used to map the multi-scale features obtained from the AR-PANet to independent channels and spatial dimensions to achieve feature refinement, thus improving the detection accuracy of small objects. Experimental results show that our proposed method can effectively improve the accuracy of small object detection in multiple datasets, addressing this challenging problem with impressive results. Thus, our proposed approach has great potential and valuable applications in the fields of remote sensing and intelligent transportation.

Abstract Background and Aims Since the beginning of the coronavirus disease 2019 (COVID‐19), a large number of government policies have been implemented worldwide in response to the global spread of COVID‐19. This paper aims at developing a data‐driven analysis to answer the three research questions: (a) Compared to the pandemic development, are the global government COVID‐19 policies sufficiently active? (b) What are the differences and characteristics in the policy activity levels at the country level? (c) What types of COVID‐19 policy patterns are forming? Methods Using the Oxford COVID‐19 Government Response Tracker data set, we present a global analysis of the COVID‐19 policy activity levels and evolution patterns from January 1, 2020 to June 30, 2022, based on the differential expression‐sliding window analysis (DE‐SWAN) algorithm and the clustering ensemble algorithm. Results Within the period under study, the results indicate that (a) the global government policy responses to COVID‐19 are very active, and the policy activity levels are significantly higher than those of global pandemic developments; (b) a high activity of policy is positively correlated to pandemic prevention at the country level; and (c) a high human development index (HDI) score is negatively correlated to the country policy activity level. Furthermore, we propose to categorize the global policy evolution patterns into three categories: (i) Mainstream (152 countries); (ii) China; and (iii) Others (34 countries). Conclusion This work is one of the few studies that quantitatively explores the evolutionary characteristics of global government policies on COVID‐19, and our results provide some new perspectives on global policy activity levels and evolution patterns.

Abstract This paper addresses the simultaneous attitude and position tracking of a rigid body subject to general bounded disturbances and input saturation in the framework of dual quaternions, which provide a compact and integrated description of the coupled rotation and translation. Treating disturbances as unknown parameters, a modular adaptive saturated pose tracking control scheme is then derived which consists of two separately designed parts. One part is the noncertainty equivalent disturbance estimator designed via the immersion and invariance method. Most existing adaptive pose controllers are based on the certainty equivalence principle. Since its parameter adaption process is unpredictable and acts like a forcing disturbance imposed on the deterministic system, it can cause arbitrary degradation of the closed‐loop performance. Instead of invoking the certainty equivalence principle, the adaption law designed based on the novel immersion and invariance method counters the effects of the uncertain parameters from a robustness perspective and eliminates the performance degradation by introducing a stable attracting manifold in the adaption process. For both constant and time‐varying disturbances, the proposed estimator can effectively attenuate their effects on the closed‐loop performance. The other part is the saturated pose tracking controller where the estimated disturbances are directly used. Based on two useful lemmas, it is proved that the saturation constraints can be removed in finite time, which enables the Lyapunov stability analysis of the closed‐loop system. Simulation results demonstrate improvements of the proposed control scheme in closed‐loop performance and control precision when compared with a certainty equivalent controller and a sliding mode controller.

Complex data pose unique challenges for data processing [...]

Abstract Background There have been no reports of tigecycline-associated drug-related liver injury (DILI) identified by histopathological assistance and causal assessment method. We reported the histopathological manifestations for the first time and described tigecycline-associated liver injury’s pattern, severity, duration, and outcome. Case presentation A 68-year-old male with post-liver transplantation was given high-dose tigecycline intravenously (loading dose 200 mg, followed by 100 mg every 12 h) combined with polymyxin B (50,000 units by aerosol inhalation every 12 h) for hospital-acquired pneumonia caused by carbapenem-resistant Klebsiella pneumoniae. At the same time, tacrolimus was discontinued. Liver function was initially normal but started to decline on day 4 of tigecycline. Reducing the dose of tigecycline and resuming tacrolimus could not reverse the deterioration. Therefore, a liver puncture biopsy was performed for further diagnosis, with histopathological findings being cytotoxic injury. The updated RUCAM scale was used to evaluate the causal relationship between tigecycline and liver injury, with the result of 7 points indicating a “probable” causality grading. Methylprednisolone was initiated to treat DILI that was determined to be Grade 1 cholestatic injury. Total bilirubin and transaminase levels returned to normal on day 4 and 11 after tigecycline withdrawal, respectively. Monthly outpatient follow-up showed that the patient’s liver function stayed normal. Conclusions This case possessed a significant reference value for differential diagnosis and treatment prognosis of tigecycline-associated DILI. With early diagnosis and timely management, the tigecycline-associated DILI of this patient was successfully reversed.

This article disclosed an authentication method for access and handover in a low-orbit satellite network intermittent connection scenario.The scheme was based on a symmetrical cryptographic system.Based on hash function, XOR operation and timestamp, the safe access of the terminal to the satellite network was ensured.It reduced signaling overhead, bandwidth overhead, and computing overhead as well.In view of the link interruption, the solution was based on the current session key between the user and satellites to quickly and safely resume communication to ensured the quality of service.Through the orbit prediction technology, according to the current session key between the user and satellites and random number, the safe switching between satellites was realized, and the communication cost during the satellite switching process was reduced.The scheme realized the anonymity of user identity, and refreshed the temporary identity for the next authentication after successful authentication.

Studying the impact of agricultural machinery services (AMS) on cultivated land productivity is conducive to scientifically improving agricultural production and has far-reaching significance for ensuring food security. Taking Handan City in the North China Plain as the research context and using a surveyed sample of 1918 farming households, this paper examines the effect of AMS on the productivity of cultivated land using OLS estimation and estimates the average treatment effect on the treated (ATT) using the propensity score matching (PSM) method. The research findings are as follows. 1) AMS has a significantly positive impact on cultivated land productivity, and a heterogeneity analysis finds that the effects are larger for farmers with relatively less cultivated land and the marginal effects decrease as the adoption of AMS increases. 2) In various planting activities, AMS adoption in basic activities (e.g., ploughing, seeding, and harvesting) has positive effects on cultivated land productivity, while AMS adoption in management activities (e.g., fertilizing, irrigation, and pesticide spraying), has no obvious effect on cultivated land productivity. 3) According to the results of ATT, the conversion of non-adopting farmers to adopting AMS would increase cultivated land productivity by 7.6%–12.1%. 4) A mechanism analysis reveals that AMS adoption relieves financial constraints, improves technical efficiency, and increases smallholders’ crop yields. These results suggest that AMS has a positive effect on cultivated land productivity and therefore have valuable policy implications for increasing smallholders’ access to various types of AMS to improve the productivity of cultivated land in regions dominated by smallholders.

This paper reviews the potential use of fuzzy c-means clustering (FCM) and explores modifications to the distance function and centroid initialization methods to enhance image segmentation. The application of interest in the paper is the segmentation of breast tumours in mammograms. Breast cancer is the second leading cause of cancer deaths in Canadian women. Early detection reduces treatment costs and offers a favourable prognosis for patients. Classical methods, like mammograms, rely on radiologists to detect cancerous tumours, which introduces the potential for human error in cancer detection. Classical methods are labour-intensive, and, hence, expensive in terms of healthcare resources. Recent research supplements classical methods with automated mammogram analysis. The basic FCM method relies upon the Euclidean distance, which is not optimal for measuring non-spherical structures. To address these limitations, we review the implementation of a Mahalanobis-distance-based FCM (FCM-M). The three objectives of the paper are: (1) review FCM, FCM-M, and three centroid initialization algorithms in the literature, (2) illustrate the effectiveness of these algorithms in image segmentation, and (3) develop a Python package with the optimized algorithms to upload onto GitHub. Image analysis of the algorithms shows that using one of the three centroid initialization algorithms enhances the performance of FCM. FCM-M produced higher clustering accuracy and outlined the tumour structure better than basic FCM.

The dilemma of aging and lack of successors must be understood to improve the scale efficiency and competitiveness of China’s agriculture. This paper uses a survey of 1347 farmers in Liaoning, Jiangsu, and Jiangxi and applies tobit and probit models to explore the impact of intergenerational inheritance on farmland management in terms of the current scale and willingness for expansion. The results show that (1) an increased probability of intergenerational inheritance in agriculture can significantly increase the scale of farmland operations, with a greater effect on the current scale than on the willingness to expand; (2) the scale upgrading effect of agricultural intergenerational inheritance is greater in regions with frequent nonagricultural activities and in families with middle or low-scale farmland operations; and (3) the promotion effect on the current scale is greater for elderly farmers 60 years old or above than for farmers who are 40–59 years old, while the promotion effect on the willingness for expansion exists only for the latter. Therefore, policies should attract young, skilled laborers to return to their hometowns for agricultural employment and entrepreneurship and support farmland transfer and scale operation in regions with frequent nonagricultural activities or a lower scale of agricultural operations.

In this paper, we focus on the homogeneity test that evaluates whether two multivariate samples come from the same distribution. This problem arises naturally in various applications, and there are many methods available in the literature. Based on data depth, several tests have been proposed for this problem but they may not be very powerful. In light of the recent development of data depth as an important measure in quality assurance, we propose two new test statistics for the multivariate two-sample homogeneity test. The proposed test statistics have the same χ2(1) asymptotic null distribution. The generalization of the proposed tests into the multivariate multisample situation is discussed as well. Simulations studies demonstrate the superior performance of the proposed tests. The test procedure is illustrated through two real data examples.

In recent years, the Poisson lognormal mixed model has been frequently used in modeling count data because it can accommodate both the over-dispersion of the data and the existence of within-subject correlation. Since the likelihood function of this model is expressed in terms of an intractable integral, estimating the parameters and obtaining inference for the parameters are challenging problems. Some approximation procedures have been proposed in the literature; however, they are computationally intensive. Moreover, the existing studies of approximate parameter inference using the Gaussian variational approximation method are usually restricted to models with only one predictor. In this paper, we consider the Poisson lognormal mixed model with more than one predictor. By extending the Gaussian variational approximation method, we derive explicit forms for the estimators of the parameters and examine their properties, including the asymptotic distributions of the estimators of the parameters. Accurate inference for the parameters is also obtained. A real-life example demonstrates the applicability of the proposed method, and simulation studies illustrate the accuracy of the proposed method.

Background: Tigecycline, a glycylcycline antibiotic, is increasingly used clinically for the treatment of severe infections caused by multidrug-resistant bacteria, but it is also associated with hepatotoxicity. However, the incidence and risk factors of tigecycline-associated drug-induced liver injury (DILI) are unclear. We conducted this study to investigate the incidence, characteristics and risk factors of tigecycline-associated DILI in the real-world clinic setting.Patients and Methods: A retrospective analysis was conducted in inpatients who received tigecycline treatment from January 2018 to January 2020. Based on the biochemical criteria of DILI and the causality assessment by Roussel Uclaf Causality Assessment Method (RUCAM) using cases with a probable or highly probable causality grading, two clinical pharmacists and one clinician worked together to screen patients for tigecycline-associated DILI. Then patients with DILI were randomly matched by gender in a ratio of 1:2 to the remaining patients in the tigecycline cohort without biochemical abnormalities to identify risk factors.Results: A total of 973 patients from 1,250 initial participants were included. The incidence of tigecycline-associated DILI was 5.7% (55/973). Among 55 DILI patients, 10 cases presented with the hepatocellular pattern, 4 cases belonged to the mixed pattern, and 41 presented with the cholestatic pattern. Most cases reached the severity of grade 1 and 2. The rate of recovery in hepatocellular pattern, mixed pattern, and cholestatic pattern was 70.0, 50.0, and 41.5%, respectively. The proportion of the DILI cases treated with high dose (100 mg) and prolonged duration (>14 days) was significantly higher than standard dose and routine duration (100.0% vs. 18.1%, p < 0.05). Logistic regression analysis showed that high maintenance dose (OR = 1.028, p = 0.002), prolonged duration (OR = 1.208, p = 0.000), and number of hepatotoxic drugs (OR = 2.232, p = 0.000) were independent factors of tigecycline-associated DILI.Conclusion: Tigecycline was associated with liver injury, with a slightly higher incidence (5.7%) than the frequency of “frequent” (5%) defined by the Medical Dictionary for Regulatory Activities. Patients with a high maintenance dose and prolonged tigecycline regimen, as well as concomitant use of multiple hepatotoxic drugs should be paid more attention.

In this paper, the fast integral terminal sliding mode control for spacecraft formation flying system is concerned subjected to external disturbances and parametric uncertainties. First, a novel modified fast integral terminal sliding mode control law is designed, which contains the advantages of fast terminal sliding mode. Then, for estimating the external disturbances in the system, the control law based on the reduced-order disturbance observer is proposed which not only reduce the order of the observer but also guarantee the tracking errors converge in finite time. Further, to identify the unknown parameters accurately, by introducing an adaptive parametric updating law, the adaptive fast integral terminal sliding mode control law is proposed, which has better robustness against external disturbances and parameter uncertainties simultaneously. Finally, the effectiveness of the proposed control laws is demonstrated by the simulation results.

A change point is a location or time at which observations or data obey two different models: before and after. In real problems, we may know some prior information about the location of the change point, say at the right or left tail of the sequence. How does one incorporate the prior information into the current cumulative sum (CUSUM) statistics? We propose a new class of weighted CUSUM statistics with three different types of quadratic weights accounting for different prior positions of the change points. One interpretation of the weights is the mean duration in a random walk. Under the normal model with known variance, the exact distributions of these statistics are explicitly expressed in terms of eigenvalues. Theoretical results about the explicit difference of the distributions are valuable. The expansions of asymptotic distributions are compared with the expansion of the limit distributions of the Cramér-von Mises statistic and the Anderson and Darling statistic. We provide some extensions from independent normal responses to more interesting models, such as graphical models, the mixture of normals, Poisson, and weakly dependent models. Simulations suggest that the proposed test statistics have better power than the graph-based statistics. We illustrate their application to a detection problem with video data.

Disputes over farmland constitute an important challenge for tenure security, economic growth and social stability. Land titling is a theoretically promising policy instrument that can enhance tenure security and reduce the occurrence of farmland disputes in the developing world. However, the impact of land titling on the occurrence of disputes has been found to be highly conditional. Empirical evidence on this issue has been surprisingly limited and has often lacked the consideration of a specific context. In this study, whether land titling affects the incidence of farmland disputes in the context of China is investigated, focusing particularly on the interaction between land titling and social capital and household capability. Both the probit and CLL models are applied, using household data entailing a total of 3693 samples located in rural China. The results show that (1) land titling in China reduces the incidence of farmland disputes, and that (2) the analysis based on interaction terms indicates that households who are disadvantaged in social capital and household capability are more likely to experience fewer disputes. Implications for the government and organizations are as follows: (1) the titling programme should seriously consider the current tenure arrangement. Confirmation of current tenure is recommended over the establishment of a new system to avoid possible institutional shopping and overlapping claims; and (2) land titling, if well implemented, is recommended to redress local power asymmetry and to help vulnerable groups defend their property.

To reduce the amount of computation in traditional model predictive current control, to improve the flexibility in choosing the direction and amplitude in the voltage vector synthesis of a dual three-phase motor by two degrees of freedom, and to reduce the output torque ripple and current ripple, this paper proposes a dual second-order model predictive control algorithm based on current loop operation optimization. Compared with the conventional speed loop using the PI control algorithm and the traditional MPC control algorithm, the proposed algorithm adopts the second-order MPC control mode in the speed loop, which decreases the speed regulation time and increases motor immunity. Meanwhile, the second-order MPC control mode is adopted in the current loop, and the traditional iterative calculation method is improved to calculate the direction and amplitude of the output voltage vector through the analytic function, which increases the flexibility of the output voltage vector. Additionally, a four-vector SVPWM is employed to modulate the voltage vector to reduce the current amplitude in the harmonic subspace. The simulation results indicate that the algorithm proposed in this paper can significantly reduce the torque ripple and the current ripple as well as increase the transient performance of the motor.

To limit the high-frequency chattering originating from the conventional sliding mode observer in a PMSM sensorless control system of vacuum pumps and reduce the steady-state error caused by the phase lag of the coordinate system on the estimated speed, a speed estimation algorithm was proposed based on the super-twisting sliding mode observer. Then, the proposed algorithm was applied to observe an electromotive force. To this end, the Lyapunov function was established to analyze the stability of the current dynamic error equation. In this regard, the estimated phase lag of the rotating coordinate system was considered to study the influence of the speed estimation error. Moreover, a speed estimation algorithm considering the d-axis estimation of back electromotive force is proposed. The performed analyses show that the speed estimation algorithm based on a super-twisting sliding mode observer has promising estimation accuracy. It is concluded that the proposed algorithm can be effectively applied to suppress high-frequency chattering in the system, reduce the influence of phase lag in the estimation coordinate system on the speed estimation error, remove the low-pass filter and phase compensation module, and improve the accuracy of speed estimation.

Medical data are often missing during epidemiological surveys and clinical trials. In this paper, we propose the MCMCINLA estimation method to account for missing data. We introduce a new latent class into the spatial lag model (SLM) and use a conditional autoregressive specification (CAR) spatial model-based approach to impute missing values, making the model fit into the integrated nested Laplace approximation (INLA) framework. Combining the advantages of both the Markov chain Monte Carlo (MCMC) and INLA frameworks, the MCMCINLA algorithm is used to implement imputation of the missing data and fit the model to derive estimates of the parameters from the posterior margins. Finally, the economic data and the hemorrhagic fever with renal syndrome (HFRS) disease data of mainland China from 2016–2018 are used as examples to explore the development of public health in China in the post-epidemic era. The results show that compared with expectation maximization (EM) and full information maximum likelihood estimation (FIML), the predicted values of the missing data obtained using our method are closer to the true values, and the spatial distribution of HFRS in China can be inferred from the imputation results with a southern-heavy and northern-light distribution. It can provide some references for the development of public health in China in the post-epidemic era.

This paper addresses the simultaneous attitude and position tracking of a target spacecraft in the presence of general unknown bounded disturbances in the framework of dual quaternions, which provides a concise and integrated description of the coupled rotational and translational motions. By virtue of the newly introduced dual direction cosine matrix, the dimension of the dual quaternion-based relative motion dynamics written in vector/matrix form can be lowered to six. Treating the disturbances as unknown parameters, a modular adaptive pose tracking control scheme composed of two separately designed parts is then derived. One part is the adaptive disturbance estimator designed based on the immersion and invariance theory. Driven by the disturbance estimation errors, it can realize exponential convergence of the estimations and has the nice “parameter lock” property, which can hardly be expected in the conventional certainty equivalent adaptive controllers. The other part is a proportional-derivative-like pose tracking controller where the estimated disturbances are directly used. The closed-loop stability of the relative motion system under different kinds of disturbances is proven by Lyapunov stability analysis. Simulations and comparisons with two previous dual quaternion-based controllers demonstrate the novel features and performance improvements of the proposed control scheme.

Abstract Background Methotrexate is an important component in many chemotherapy protocols. The blood concentration of Methotrexate is used to determine the regimen of folinic acid. However, the lower limit of Siemens assay kit is 0.30 μmol/L in China. This study extended the limit from 0.3 to 0.05 μmol/L and reduced the test cost by optimizing the parameters of Enzyme Multiplied Immunoassay Technique assay. Methods Parameters of Enzyme Multiplied Immunoassay Technique assay were modified to decrease the volume of reagents A and B. Then a standard curve with a new custom set of calibrators was prepared to detect low concentration. Intra-day and inter-day imprecision were assessed by control material and samples. The linearity of the modified assay was verified by analyzing a range of quality controls with known concentration from 0.05 to 1.00 μmol/L. At last, the same samples were tested by modified Enzyme Multiplied Immunoassay Technique assay and Liquid Chromatography-tandem Mass Spectrometry assay respectively. A simple linear regression was performed to verify the validity of the modified Enzyme Multiplied Immunoassay Technique assay. Results Intra-day and inter-day imprecision show good reproducibility at all levels (0.05, 0.12, 0.43, 0.82 μmol/L). The linearity equation of modified assay was y = 0.9913x + 0.0046, in which y was the mean of measured concentration and x was the target concentration (R2 = 0.9994). In the range of 0.05–10.00 μmol/L, correlation between the Modified assay and Liquid Chromatography-tandem Mass Spectrometry assay was significant (r = 0.9968). In the range of 0.30–10.00 μmol/L, the correlation between modified and commercial assays was significant (r = 0.9987) as well. Conclusions The modified assay enhanced the sensitivity of Siemens VIVA-E to 0.05 μmol/L. In addition, the test number of a reagent Kit increased from 140 to 210. This means the cost of detection was reduced about 30%.

In this paper, a nonsingular fast terminal adaptive neurosliding mode control for spacecraft formation flying systems is investigated. First, a supertwisting disturbance observer is employed to estimate external disturbances in the system. Second, a fast nonsingular terminal sliding mode control law is proposed to guarantee the tracking errors of the spacecraft formation converge to zero in finite time. Third, for the unknown parts in the spacecraft formation flying dynamics, we proposed an adaptive neurosliding mode control law to compensate them. The proposed sliding mode control laws not only achieve the formation but also alleviate the effect of the chattering. Finally, simulations are used to demonstrate the effectiveness of the proposed control laws.

Objectives A failed first attempt at laryngeal mask airway (LMA) insertion could increase the risk of laryngospasm, hypoxemia, and postoperative sore throat. This study was performed to investigate the risk factors for failed first-attempt LMA placement. Methods In total, 461 patients who underwent general anesthesia with a Supreme LMA (Teleflex Medical, Shanghai, China) and who had an American Society of Anesthesiologists (ASA) physical status of I to III were prospectively enrolled. The LMA was inserted after anesthetic induction. We recorded the insertion conditions and each patient’s age, ASA status, body weight, body mass index (BMI), duration of anesthesia, size of LMA, and cuff pressure; the years of work experience of the anesthesiologists; and the use or nonuse of lidocaine gel as a lubricant. Results Successful first-attempt placement of the Supreme LMA was achieved in 438 (95.10%) patients, while first-attempt placement failed in 23 (4.99%). Significant risk factors for failure of first-attempt LMA insertion included high age, high body weight, BMI of 61 years, high body weight, BMI of