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This paper aims to present a novel adaptive sliding mode control (ASMC) method based on the predefined performance barrier function for reusable launch vehicle under attitude constraints and mismatched disturbances.

A novel ASMC based on barrier function is adopted to deal with matched and mismatched disturbances. The upper bounds of the disturbances are not required to be known in advance. Meanwhile, a predefined performance function (PPF) with prescribed convergence time is used to adjust the boundary of the barrier function. The transient performance, including the overshoot, convergence rate and settling time, as well as the steady-state performance of the attitude tracking error are retained in the predetermined region under the barrier function and PPF. The stability of the proposed control method is analyzed via Lyapunov method.

In contrast to conventional adaptive back-stepping methods, the proposed method is comparatively simple and effective which does not need to disassemble the control system into multiple first-order systems. The proposed barrier function based on PPF can adjust not only the switching gain in an adaptive way but also the convergence time and steady-state error. And the efficiency of the proposed method is illustrated by conducting numerical simulations.

A novel barrier function based ASMC method is proposed to fit in the amplitude of the mismatched and matched disturbances. The transient and steady-state performance of attitude tracking error can be selected as prior control parameters.

A chaotic home environment, marked by disorganization, noise and a lack of routine, has negative associations with language development, social competence and executive functioning. This study aims to investigate the mediating effect of chaotic homes on adaptive behaviors, or behaviors that allow independent functioning, in children diagnosed with autism spectrum disorder (ASD) compared to neurotypical (NT) children. Children with ASD have difficulties with adaptive functioning in their environment, and identifying factors in the home that may exacerbate these behaviors will help in understanding the larger family dynamics that may affect behavior.

In total, 251 primary caregivers completed questionnaires about their children’s adaptive behavior and the structure of the home environment.

The results of a mediation analysis found a significant indirect effect of ASD status leading to lower adaptive behaviors through home chaos. This suggests those with ASD experienced more household chaos than NT children, which influenced their lower adaptive behavior scores.

This research provides insights into the complex relationship between the home environment and child behavior in children with ASD.

In the final step, the trust model is applied to the on-demand federated multipath distance vector routing protocol (AOMDV) to introduce path trust as a foundation for routing selection in the route discovery phase, construct a trusted path, and implement a path warning mechanism to detect malicious nodes in the route maintenance phase, respectively.

A trust-based on-demand multipath distance vector routing protocol is being developed to address the problem of flying ad-hoc network being subjected to internal attacks and experiencing frequent connection interruptions. Following the construction of the node trust assessment model and the presentation of trust evaluation criteria, the data packet forwarding rate, trusted interaction degree and detection packet receipt rate are discussed. In the next step, the direct trust degree of the adaptive fuzzy trust aggregation network compute node is constructed. After then, rely on the indirect trust degree of neighbouring nodes to calculate the trust degree of the node in the network. Design a trust fluctuation penalty mechanism, as a second step, to defend against the switch attack in the trust model.

When compared to the lightweight trust-enhanced routing protocol (TEAOMDV), it significantly improves the data packet delivery rate and throughput of the network significantly.

Additionally, it reduces the amount of routing overhead and the average end-to-end delay.

This paper aims to investigate the law and logic mechanism of management control matching pattern and company strategy aggressiveness under different strategies by textual analysis, based on the empirical data of Chinese A-share listed companies during the period from 2010 to 2018. Additional analyses further investigate the moderating effect of environmental uncertainty and R&D intensity on the relationship between management control matching type and strategy aggressiveness. The conclusion can help relevant departments to develop management control theory and method system with Chinese characteristics and provide theoretical reference for the matching mode of dual control.

This paper uses the text analysis method. The main explanatory variables are analyzed using the computer SQL Server database software through the relevant text of the board of directors report in the company annual report. Other financial data came from the CSMAR database, excluding ST and PT and companies with missing data, and 16,902 samples were finally obtained. This paper conducted statistical analysis through Stata12.

This paper shows that the matching pattern between formal and informal control is divided into three types. They have different impacts on strategy aggressiveness. Specifically, consistent matching type II significantly positively influences the aggressiveness of offensive strategy. Consistent matching type I significantly positively influences the aggressiveness of defensive strategy. Complementary matching type I significantly positively influences the aggressiveness of analytical strategy. Additional analyses find that compared with non-high-tech companies, high-tech companies have more significant influence on the relationship between management control matching pattern and company strategic aggressiveness. And compared with other two “strategy-control” matching patterns, both environmental uncertainty and product innovation have more significant influence on the relationship between consistent matching II and offensive strategy aggressiveness.

To the best of the authors’ knowledge, this paper divides the formal and informal control matching patterns of management control into three categories for the first time. It examines the relationship between the formal and informal control matching of management accounting and the degree of strategy aggressiveness. The conclusion provides new empirical evidence to promote the effective implementation of development strategies for companies. It can help relevant departments to develop management control theory and method systems with Chinese characteristics and provide theoretical references for the matching mode of dual control.

Bayesian cubature (BC) has emerged to be one of most competitive approach for estimating the multi-dimensional integral especially when the integrand is expensive to evaluate, and alternative acquisition functions, such as the Posterior Variance Contribution (PVC) function, have been developed for adaptive experiment design of the integration points. However, those sequential design strategies also prevent BC from being implemented in a parallel scheme. Therefore, this paper aims at developing a parallelized adaptive BC method to further improve the computational efficiency.

By theoretically examining the multimodal behavior of the PVC function, it is concluded that the multiple local maxima all have important contribution to the integration accuracy as can be selected as design points, providing a practical way for parallelization of the adaptive BC. Inspired by the above finding, four multimodal optimization algorithms, including one newly developed in this work, are then introduced for finding multiple local maxima of the PVC function in one run, and further for parallel implementation of the adaptive BC.

The superiority of the parallel schemes and the performance of the four multimodal optimization algorithms are then demonstrated and compared with the k-means clustering method by using two numerical benchmarks and two engineering examples.

Multimodal behavior of acquisition function for BC is comprehensively investigated. All the local maxima of the acquisition function contribute to adaptive BC accuracy. Parallelization of adaptive BC is realized with four multimodal optimization methods.

Zara et al. (2023) provide novel findings into how psychopathy may develop, showing that early life predictors of poor relationships (e.g. being unwanted before birth) are predictive of psychopathy in adulthood. The authors provide a theoretical interpretation of why psychopathy might develop based on these findings by using an adaptive perspective, suggesting that psychopathy may protect or shield individuals from poor relationships. This commentary aims to critically evaluate and extend this latter suggestion in hopes of fostering further research and clarity on the topic.

After presenting an overview of evolutionary perspectives, a summary and elaboration are presented of the interpretation that psychopathy may be an adaptive response that functions to protect individuals from poor relationships. Then, an additional adaptive interpretation is offered.

Psychopathy describes a collection of traits and behavior that facilitates an approach-oriented and exploitative motivational style that might suggest more than a protective function. When negative or poor relationships are experienced (e.g. being unwanted), it is suggested that psychopathy may begin to develop not just for protection (If I am not loved, I will shield myself from those around me) but to actively orient toward exploitation (If I am not loved, I will exploit those around me).

This commentary hopes to arouse further interest into the theoretical interpretations of why psychopathy may develop that are based on findings of how psychopathy develops. These considerations are consequential for understanding what to target in treatments that aim to meet the specific needs and motivations of individuals with psychopathic traits.

The purpose of this research study was to explore the relationship between adaptive performance and work-related indicators of psychological well-being among ‘The Episcopal Church bishops.’

Hierarchical regression models were used in this research study to explore the relationship between adaptive performance and work-related psychological health.

There was a positive correlation between adaptive performance and work-related psychological health. Demographic factors did not correlate to adaptive performance. However, a negative correlation was observed between the years ordained as a bishop and the interpersonal adaptability dimension of adaptive performance.

Managing work stress has been revealed as an integral part of adaptive performance and satisfaction in ministry. Interpersonal adaptability and reactivity could be understood, then, as useful vehicles for increasing the capacity of bishops to manage work stress. In this research, the authors applied the Scale for Individual Adaptive Performance and the two scales Scale of Satisfaction in Ministry and Scale of Emotional Exhaustion in Ministry .

The results provided insights into the behaviors necessary for adequate development of bishops in their role. The religious landscape was becoming more challenging from a revenue generation perspective. The resultant complexity and the financial strain would necessitate the need for development of different models of ministry for long-term sustainability. This could further necessitate a different set of knowledge creation related to a set of behavioral capacities like those of adaptive performance. Such insights would assist in the promotion and development of greater work-related psychological health in bishops while deepening their ability to deal with complex and uncertain environments. Furthermore, this would increase satisfaction in ministry through improved workplace management skills.

Presently, very few studies empirically established the developmental needs of bishops as they entered, learned and grew into their leadership roles. Such insights would allow the formation programs for new bishops to be grounded in empirical data. Furthermore, this research study examined a largely unexplored population. This would provide a basis for a larger research agenda related to adaptive performance in judicatory leaders and their work-related psychological health. Consequently, it is posited that improved psychological health would result in better workplace learning.

Quadrotors have been applied in various fields. However, because the quadrotor is subject to multiple disturbances, consisting of external disturbances, actuator faults and parameter uncertainties, it is difficult to control the unmanned aerial vehicle (UAV) to achieve high-precision tracking performance. This paper aims to design a safety controller that uses observer and neural network method to improve the tracking performance of UAV under multiple disturbances. The experiments prove that this method is effective.

First, to actively estimate and compensate the synthetic uncertainties of the system, a finite-time extended state observer is investigated, and the disturbances are transformed into the extended state of the system for estimation. Second, an adaptive neural network controller that does not accurately require the dynamic model knowledge is designed based on the estimated value, where the weights of the neural network can be dynamically adjusted by the adaptive law. Furthermore, the finite-time bounded convergence of the proposed observer and the stability of the system are proved through homogeneous theory and Lyapunov method.

The figure-“8” climbing flight simulation and real flight experiments illustrate that the proposed safety control strategy has good tracking performance.

This paper proposes the safety control structure of the UAV, which combines the extended state observer with the neural network method. Numerical simulation results and actual flight experiments demonstrate the effectiveness of the proposed control strategy.

The present research attempts to show the contribution of emotional intelligence and servant leadership climate to individual adaptive performance. The authors intend to explain the relations between the emotional intelligence of employees as well as of manager and the employee's adaptive performance. Moreover, this research assesses the significance of the mediating role of “servant leadership” climate in the relationship between the emotional intelligence of the manager and the employee's adaptive performance.

This research uses the quantitative research method and is included in explanatory research. Data collection used several informants for each organization. Data were collected using a sample of 57 managers and 204 team members spread over 24 companies belonging to different sectors of activity.

Employees' emotional intelligence directly influences individual adaptive performance. There is a direct influence of manager's emotional intelligence on individual adaptive performance. Then, there is an indirect influence of emotional intelligence on individual adaptive performance through the mediation of servant leadership climate.

The novelty of this research is in its effort to observe the multilevel mediation of servant leadership climate with other variables developed in the research model. No previous studies have found a relationship between employee and manager's emotional intelligence and individual adaptive performance.

COVID-19 has occurred in more than 150 countries and causes a huge impact on the health of many people. The main purpose of this work is, COVID-19 has occurred in more than 150 countries and causes a huge impact on the health of many people. The COVID-19 diagnosis is required to detect at the beginning stage and special attention should be given to them. The fastest way to detect the COVID-19 infected patients is detecting through radiology and radiography images. The few early studies describe the particular abnormalities of the infected patients in the chest radiograms. Even though some of the challenges occur in concluding the viral infection traces in X-ray images, the convolutional neural network (CNN) can determine the patterns of data between the normal and infected X-rays that increase the detection rate. Therefore, the researchers are focusing on developing a deep learning-based detection model.

The main intention of this proposal is to develop the enhanced lung segmentation and classification of diagnosing the COVID-19. The main processes of the proposed model are image pre-processing, lung segmentation and deep classification. Initially, the image enhancement is performed by contrast enhancement and filtering approaches. Once the image is pre-processed, the optimal lung segmentation is done by the adaptive fuzzy-based region growing (AFRG) technique, in which the constant function for fusion is optimized by the modified deer hunting optimization algorithm (M-DHOA). Further, a well-performing deep learning algorithm termed adaptive CNN (A-CNN) is adopted for performing the classification, in which the hidden neurons are tuned by the proposed DHOA to enhance the detection accuracy. The simulation results illustrate that the proposed model has more possibilities to increase the COVID-19 testing methods on the publicly available data sets.

From the experimental analysis, the accuracy of the proposed M-DHOA–CNN was 5.84%, 5.23%, 6.25% and 8.33% superior to recurrent neural network, neural networks, support vector machine and K-nearest neighbor, respectively. Thus, the segmentation and classification performance of the developed COVID-19 diagnosis by AFRG and A-CNN has outperformed the existing techniques.

This paper adopts the latest optimization algorithm called M-DHOA to improve the performance of lung segmentation and classification in COVID-19 diagnosis using adaptive K-means with region growing fusion and A-CNN. To the best of the authors’ knowledge, this is the first work that uses M-DHOA for improved segmentation and classification steps for increasing the convergence rate of diagnosis.