Seismic coherence is commonly used to delineate structural and stratigraphic discontinuities. We generally use full-bandwidth seismic data to calculate coherence. However, some seismic stratigraphic features may be buried in this full-bandwidth data but can be highlighted by certain spectral components. Due to thin-bed tuning phenomena, discontinuities in a thicker stratigraphic feature may be tuned and thus better delineated at a lower frequency, whereas discontinuities in the thinner units may be tuned and thus better delineated at a higher frequency. Additionally, whether (...) due to the seismic data quality or underlying geology, certain spectral components exhibit higher quality over other components, resulting in correspondingly higher quality coherence images. Multispectral coherence provides an effective tool to exploit these observations. We have developed the performance of multispectral coherence using different spectral decomposition methods: the continuous wavelet transform, maximum entropy, amplitude volume technique, and spectral probe. Applications to a 3D seismic data volume indicate that multispectral coherence images are superior to full-bandwidth coherence, providing better delineation of incised channels with less noise. From the CWT experiments, we find that providing exponentially spaced CWT components provides better coherence images than equally spaced components for the same computation cost. The multispectral coherence image computed using maximum entropy spectral voices further improves the resolution of the thinner channels and small-scale features. The coherence from AVT data set provides continuous images of thicker channel boundaries but poor images of the small-scale features inside the thicker channels. Additionally, multispectral coherence computed using the nonlinear spectral probes exhibits more balanced and reveals clear small-scale geologic features inside the thicker channel. However, because amplitudes are not preserved in the nonlinear spectral probe decomposition, noise in the noisier shorter period components has an equal weight when building the covariance matrix, resulting in increased noise in the generated multispectral coherence images. (shrink)

Over recent years, the issue of corruption in the public construction sector has attracted increasing attention from both practitioners and researchers worldwide. However, limited efforts are available for investigating the underlying factors of corruption in this sector. Thus, this study attempted to bridge this knowledge gap by exploring the underlying factors of corruption in the public construction sector of China. To achieve this goal, a total of 14 structured interviews were first carried out, and a questionnaire survey was then administered (...) to 188 professionals in China. Two iterations of multivariate analysis approaches, namely, stepwise multiple regression analysis and partial least squares structural equation modeling were successively utilized to analyze the collected data. In addition, a case study was also conducted to triangulate the findings obtained from the statistical analysis. The results generated from these three research methods achieve the same conclusion: the most influential underlying factor leading to corruption was immorality, followed by opacity, unfairness, procedural violation, and contractual violation. This study has contributed to the body of knowledge by exploring the properties of corruption in the public construction sector. The findings from this study are also valuable to the construction authorities as they can assist in developing more effective anti-corruption strategies. (shrink)

Over recent years, the issue of corruption in the public construction sector has attracted increasing attention from both practitioners and researchers worldwide. However, limited efforts are available for investigating the underlying factors of corruption in this sector. Thus, this study attempted to bridge this knowledge gap by exploring the underlying factors of corruption in the public construction sector of China. To achieve this goal, a total of 14 structured interviews were first carried out, and a questionnaire survey was then administered (...) to 188 professionals in China. Two iterations of multivariate analysis approaches, namely, stepwise multiple regression analysis and partial least squares structural equation modeling were successively utilized to analyze the collected data. In addition, a case study was also conducted to triangulate the findings obtained from the statistical analysis. The results generated from these three research methods achieve the same conclusion: the most influential underlying factor leading to corruption was immorality, followed by opacity, unfairness, procedural violation, and contractual violation. This study has contributed to the body of knowledge by exploring the properties of corruption in the public construction sector. The findings from this study are also valuable to the construction authorities as they can assist in developing more effective anti-corruption strategies. (shrink)

Response strategy is a key for preventing widespread corruption vulnerabilities in the public construction sector. Although several studies have been devoted to this area, the effectiveness of response strategies has seldom been evaluated in China. This study aims to fill this gap by investigating the effectiveness of response strategies for corruption vulnerabilities through a survey in the Chinese public construction sector. Survey data obtained from selected experts involved in the Chinese public construction sector were analyzed by factor analysis and partial (...) least squares-structural equation modeling. Analysis results showed that four response strategies of leadership, rules and regulations, training, and sanctions, only achieved an acceptable level in preventing corruption vulnerabilities in the Chinese public construction sector. This study contributes to knowledge by improving the understanding of the effectiveness of response strategies for corruption vulnerabilities in the public construction sector of developing countries. (shrink)

By coupling a diode bridge-based second-order memristor and an active voltage-controlled memristor with a capacitor, a three-element-based memristive circuit is synthesized and its system model is then built. The boundedness of the three-element-based memristive circuit is theoretically proved by employing the contraction mapping principle. Besides, the stability distributions of equilibrium points are theoretically and numerically expounded in a 2D parameter plane. The results imply the memristive circuit has a zero unstable saddle focus and a pair of nonzero stable node-foci or (...) unstable saddle-foci depending on the considered parameters. The dynamical behaviors include point attractor, period, chaos, coexisting bifurcation mode, period-doubling bifurcation route, and crisis scenarios, which are explored using some common dynamical methods. Of particular concern, riddled attraction basins and multistability are uncovered under two sets of specified model parameters nearing the tiny neighborhood of crisis scenarios by local attraction basins and phase plane plots. The riddled attraction basins with island-like structure demonstrate that their dynamical behaviors are extremely sensitive to the initial conditions, resulting in the coexistence of limit cycles with period-2 and period-6, as well as the coexistence of period-1 limit cycles and single-scroll chaotic attractors. Moreover, a feasible on-breadboard hardware circuit is manually made and the experimental measurements are executed, upon which phase plane trajectories for some discrete model parameters are captured to further confirm the numerically simulated ones. (shrink)

Disordered industrial expansion in a given region leads to the excessive consumption of resources and environmental deterioration. Therefore, the influence of the regional industrial structure and layout on the resource environmental carrying capacity is receiving attention. This study constructs a comprehensive analytical framework of the industries, population, the economy, resources, and the environment. This framework evaluates the importance of each industry with respect to regional socioeconomic development; furthermore, it classifies industries based on the evaluation results and assumes various development scenarios (...) for industrial restructuring. Based on ArcGIS spatial analysis tool, this study analyzes the consumption of resources and the environment in each township under the current development scenario. In addition, this study provides basic support for the optimization of the industrial space layout. The RECC is assessed under different development scenarios, and the results provide a basis for industrial restructuring. The results show that the Jingcheng Subdistrict consumes the most resources and environment among all the township units. However, since it has the highest GDP, it consumes the least resources and the environment per unit GDP overall. The results also show that the RECC with the development of the petroleum, coking, and nuclear fuel processing products industry can maximize the RECC of Jingjiang. The analytical framework in this study effectively connects regional industrial restructuring to the RECC, which can enhance the operability of the decision support. (shrink)

The diverse value of rural areas has been gradually highlighted, and promoting the sustainable development of rural areas with the theoretical guidance of rural multifunction is the key to realizing rural revitalization. This study defined the concept of rural multifunction from the perspective of resident’s demands and divided it into five main functions including rural agricultural production, nonagricultural production, living, ecological environment, and social security. By constructing the evaluation index system of rural multifunction, we analysed the spatial distribution characteristics of (...) 160 villages of Jingjiang in Jiangsu Province. And functional combinations were identified to select targeted rural development paths oriented by balanced development of rural multifunction. The results showed the following. The development of various rural functions in Jingjiang city was uneven, and agricultural production function still dominated. The villages with strong agricultural production function were mainly concentrated in the northwest, while the villages with a high level of nonagricultural production function were mostly distributed in the industrial parks or around towns. There is still much room for improvement in social security function, especially in areas dominated by nonagricultural production. Nonagricultural production function had a negative effect on the ecological environment function, which is contrary to the agricultural production function. Balanced development rather than equal development of rural functions should be pursued to achieve multifunctionality. Scientific guidance for the functional growth of villages in Jingjiang city and theoretical support for the microscale evaluation of rural multifunction and its application were provided by the research results. (shrink)

In this paper, the security analysis of a color image encryption algorithm based on Hopfield chaotic neural network is given. The original chaotic image encryption algorithm includes permutation encryption and diffusion encryption. The result of cryptanalysis shows that the chaotic sequences generated by this algorithm are independent of plaintext image, and there exist equivalent permutation key and equivalent diffusion key. Therefore, according to chosen-plaintext attack, the equivalent diffusion key and the equivalent permutation key can be obtained by choosing two special (...) plaintext images and the corresponding ciphertext images, respectively, and the plaintext image is further recovered from the ciphertext image. Theoretical analysis and numerical simulation experiment results verify the effectiveness of the analytical method. Finally, some improved suggestions for the original encryption algorithm are proposed to promote the security. (shrink)

Recently, as a highly infectious disease of novel coronavirus has swept the globe, more and more patients need to be isolated in the rooms of the hospitals, so how to deliver the meals or drugs to these infectious patients is the urgent work. It is a reliable and effective method to transport medical supplies or meals to patients using robots, but how to teach the robot to the destination and to enter the door like a human is an exciting task. (...) In this paper, a novel human-like control framework for the mobile medical service robot is considered, where a Kinect sensor is used to manage human activity recognition to generate a designed teaching trajectory. Meanwhile, the learning technique of dynamic movement primitives with the Gaussian mixture model is applied to transfer the skill from humans to robots. A neural-based model predictive tracking controller is implemented to follow the teaching trajectory. Finally, some demonstrations are carried out in a hospital room to illustrate the superiority and effectiveness of the developed framework. (shrink)

Robot manipulators have been extensively used in complex environments to complete diverse tasks. The teleoperation control based on human-like adaptivity in the robot manipulator is a growing and challenging field. This paper developed a disturbance-observer-based fuzzy control framework for a robot manipulator using an electromyography- driven neuromusculoskeletal model. The motion intention was estimated by the EMG-driven NMS model with EMG signals and joint angles from the user. The desired torque was transmitted into the desired velocity for the robot manipulator system (...) through an admittance filter. In the robot manipulator system, a fuzzy logic system, utilizing an integral Lyapunov function, was applied for robot manipulator systems subject to model uncertainties and external disturbances. To compensate for the external disturbances, fuzzy approximation errors, and nonlinear dynamics, a disturbance observer was integrated into the controller. The developed control algorithm was validated with a 2-DOFs robot manipulator in simulation. The results indicate the proposed control framework is effective and crucial for the applications in robot manipulator control. (shrink)

Mobile manipulators are widely used in different fields for transferring and grasping tasks such as in medical assisting devices, industrial production, and hotel services. It is challenging to improve navigation accuracies and grasping success rates in complex environments. In this paper, we develop a multisensor-based mobile grasping system which is configured with a vision system and a novel gripper set in an UR5 manipulator. Additionally, an error term of a cost function based on DWA is proposed to improve the navigation (...) performance of the mobile platform through visual guidance. In the process of mobile grasping, the size and position of the object can be identified by a visual recognition algorithm, and then the finger space and chassis position can be automatically adjusted; thus, the object can be grasped by the UR5 manipulator and gripper. To demonstrate the proposed methods, comparison experiments are also conducted using our developed mobile grasping system. According to the analysis of the experimental results, the motion accuracy of the mobile chassis has been improved significantly, satisfying the requirements of navigation and grasping success rates, as well as achieving a high performance over a wide grasping size range from 1.7 mm to 200 mm. (shrink)

A pathogenic connection between autoreactive T cells, fungal infection, and carcinogenesis has been demonstrated in studies of human autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy as well as in a mouse model in which kinase-dead Ikkα knock-in mice develop impaired central tolerance, autoreactive T cell–mediated autoimmunity, chronic fungal infection, and esophageal squamous cell carcinoma, which recapitulates APECED. IκB kinase α is one subunit of the IKK complex required for NF-κB activation. IKK/NF-κB is essential for central tolerance establishment by regulating the development of medullary thymic (...) epithelial cells that facilitate the deletion of autoreactive T cells in the thymus. In this review, we extensively discuss the pathogenic roles of inborn errors in the IKK/NF-κB loci in the phenotypically related diseases APECED, immune deficiency syndrome, and severe combined immunodeficiency; differentiate how IKK/NF-κB components, through mTEC, T cells/leukocytes, or epithelial cells, contribute to the pathogenesis of infectious diseases, autoimmunity, and cancer; and highlight the medical significance of IKK/NF-κB in these diseases. IKK/NF-κB regulates the expression of many genes that encode proteins involved in many crucial biological functions, such as immunity, tissue homeostasis, and fungal/bacterial/viral infections. Also, IKKα plays anti-tumor activities in many organs independently of NF-κB pathways. Thus, an inborn error in one of these gene loci can cause severe human diseases through these complicated mechanisms. (shrink)