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This paper aims to present an adaptive fuzzy sliding mode controller with nonlinear observer (AFSMCO) for the redundant robotic manipulator handling a varying payload to achieve a precise trajectory tracking in the task space. This approach could be applied to solve the problems caused by the dynamic effect of the varying payload to robotic system caused by model uncertainties.

First, a suitable observer using the recursive algorithm is presented for an accurate estimation of external disturbances caused by a variable payload. Second, the adaptive fuzzy logic is designed to approximate the parameters of the sliding mode controller combined with nonlinear observer (SMCO) to avoid chattering in real time. Moreover, Lyapunov theory is applied to guarantee the stability of the proposed closed-loop robotic system. Finally, the effectiveness of the proposed control approach and theoretical discussion are proved by simulation results on a seven-link robot and demonstrated by a humanoid robot platform.

The varying payload leads to large variations in the dynamics of the manipulator and the tracking error. To achieve high-precision position tracking, nonlinear observer was introduced to feed into the sliding mode control (SMC) which had improved the ability to resist the external disturbance. In addition, the chattering caused by the SMC was eliminated by recursively approximating the switching gain with the usage of adaptive fuzzy logic. Therefore, a distributed control strategy solves the problems of an SMC implementation in improving its tracking performance and eliminating the chattering of the system control.

The AFSMCO is proposed for the first time and used to control the redundant robotic manipulator that handles the varying payload. The proposed control algorithm possesses better robustness and higher precision for the trajectory tracking than classical SMC.

Robot kinematic modeling needs to be based on clear physical concepts. The widely used Denavit–Hartenberg (D–H) convention requires the coordinate system to be established on an extension of the axis. This leads to non-trivial problems which this study seeks to address by developing an improved convention.

First, the problems associated with the traditional D–H convention are systematically analyzed. Then, pursuant of solving these problems, an enhanced Denavit–Hartenberg (ED–H) convention is proposed, and a procedure is delineated for establishing the coordinate frame and obtaining the associated parameters. The transformation equations are derived based on a homogeneous matrix. The characteristics of traditional D–H and ED–H with regard to kinematics and dynamics are comprehensively compared. Finally, an application of dynamics for lead-through programming and collision protection is undertaken to validate the proposed ED–H method. Simulations and experiments are carried out using the Tiansui-One cooperative robot platform with the aim of exploring the merits of the proposed convention.

The proposed convention is compatible with traditional methods and can solve the problems inherent in these methods. The main characteristic of ED–H is that the coordinate system is fixed on the joint, which is a general modeling method.

An enhanced D–H convention is proposed to establish a unified, intuitive and accurate link model that exhibits stronger adaptability than traditional D–H and can be used effectively in kinematic and dynamic modeling of mechanical arms.

Walking on inclined ground is an important ability for humanoid robots. In general, conventional strategies for walking on slopes lack technical analysis in, first, the waist posture with respect to actual robot and, second, the landing impact, which weakens the walking stability. The purpose of this paper is to propose a generic method for walking pattern generation considering these issues with the aim of enabling humanoid robot to walk dynamically on a slope.

First, a virtual ground method (VGM) is proposed to give a continuous and intuitive zero-moment point (ZMP) on slopes. Then, the dynamic motion equations are derived based on 2D and 3D models, respectively, by using VGM. Furthermore, the waist posture with respect to the actual robot is analyzed. Finally, a reformative linear inverted pendulum (LIP) named the asymmetric linear inverted pendulum (ALIP) is proposed to achieve stable and dynamical walking in any direction on a slope with lower landing impact.

Simulations and experiments are carried out using the DRC-XT humanoid robot platform with the aim of verifying the validity and feasibility of these new methods. ALIP with consideration of waist posture is practical in extending the ability of walking on slopes for humanoid robots.

A generic method called ALIP for humanoid robots walking on slopes is proposed. ALIP is based on LIP and several changes, including model analysis, motion equations and ZMP functions, are discussed.

Humanoid robots should have the ability of walking in complex environment and overcoming large obstacles in rescue mission. Previous research mainly discusses the problem of humanoid robots stepping over or on/off one obstacle statically or dynamically. As an extreme case, this paper aims to demonstrate how the robots can step over two large obstacles continuously.

The robot model uses linear inverted pendulum (LIP) model. The motion planning procedure includes feasibility analysis with constraints, footprints planning, legs trajectory planning with collision-free constraint, foot trajectory adapter and upper body motion planning.

The motion planning with the motion constraints is a key problem, which can be considered as global optimization issue with collision-free constraint, kinematic limits and balance constraint. With the given obstacles, the robot first needs to determine whether it can achieve stepping over, if feasible, and then the robot gets the motion trajectory for the legs, waist and upper body using consecutive obstacles stepping over planning algorithm which is presented in this paper.

The consecutive stepping over problem is proposed in this paper. First, the paper defines two consecutive stepping over conditions, sparse stepping over (SSO) and tight stepping over (TSO). Then, a novel feasibility analysis method with condition (SSO/TSO) decision criterion is proposed for consecutive obstacles stepping over. The feasibility analysis method’s output is walking parameters with obstacles’ information. Furthermore, a modified legs trajectory planning method with center of mass trajectory compensation using upper body motion is proposed. Finally, simulations and experiments for SSO and TSO are carried out by using the XT-I humanoid robot platform with the aim to verify the validity and feasibility of the novel methods proposed in this paper.

Mechatronics is a very important area of research in industrial applications. The purpose of this study is to find some of the most important components of the literature on this subject.

The analysis is based on the use of the database Compendex; it was searched in the broadest way for documents related to mechatronics. In addition, subject guides from libraries of universities with mechatronics programs were studied to find resources available in those areas.

The literature of mechatronics is extensive and multidisciplinary. Based on the results from Compendex, the following data were found: most productive authors, list of leading journals and conference proceedings, publishers and grant organizations, authors’ affiliations and other minor details. Based on the analysis of subject guides, the following types of resources were found: research databases, reference books and ebook collections.

Part of the analysis is based on a search performed in one technical database, Compendex; it was the database that generated the largest number of citations as compared to Inspec and the Web of Science. The results have a strong English language focus. It is possible that by using the results from multiple data bases, some additional sources could be obtained.

Mechatronics is a relatively new technological field comprising a number of scientific and engineering areas. The results obtained summarized a significant amount of bibliographic information.

The work is original; to the best of the authors’ knowledge, no other study has analyzed the literature on this subject.

Post-traumatic stress disorder (PTSD) is associated with risk of suicide and chronic psychological impairment. The continued exposure to stress suffered by health-care workers (HCWs) during the COVID-19 pandemic can be considered a mass traumatic event and contribute to higher rates of PTSD in this population. The purpose of this research is to find out the prevalence and factors associated with PTSD among HCW in a general hospital.

The authors devised a survey to assess the prevalence of PTSD among HCWs in a general hospital and its relationship with sex, social support, profession, work experience in health care, time spent caring for COVID-19 patients and place in which the COVID-19-related activities were carried out. PTSD symptoms were assessed using the PCL-5, Portuguese version.

A total of 226 HCWs were included in the study. Provisional diagnosis of PTSD was made based on the PCL-5 responses, considering DSM-5 criteria and the cutoff score of 33. In total, 79 (35.0%) HCWs had a provisional diagnosis of PTSD, and a significant association was found between PTSD and time spent working with COVID-19 patients and between PTSD and place of work, namely, the COVID-19 emergency room and intensive care unit.

The results highlight the need for a reflection on the importance of mental health promotion among HCWs, specially in adverse conditions such as the current pandemic.

As a consequence of new public management reforms, leading professionals in public service organizations have increasingly been involved in management roles. The phenomenon of clinical directors in the healthcare sector is particularly representative of this, as this medical manager role has been adopted in many countries around the world. However, professionals’ managerial role taking still falls quite short of expectations. While most research has searched for the causes of this gap at the individual level by exploring the clash between management and professionalism, the purpose of the paper is to argue that a contextualized understanding of the antecedents at the organizational level, and particularly the existing medical management roles, provides a more thorough picture of the reality.

The paper adopts an institutional perspective to study the development of existing medical management roles and the rise of new ones (clinical directors). The analysis focuses on the case of Italy, a country with a tradition in medical management where, following the example of other countries, clinical director roles were introduced by law; yet they were not incisive. The paper is based on a review of the existing literature and extensive field research on Italian clinical directorates.

The paper shows how in contexts in which doctors in management roles exist and are provided with legitimacy deriving from legal norms, historical settlements between professions and taken for granted arrangements, medical management becomes institutionalized, stability prevails and change towards new doctor-in-management roles is seriously hampered.

The paper contributes to existing knowledge on professionals’ managerial role taking, underlining the relevance of contextual and nation-specific factors on this process. It provides implications for research and for policy making in healthcare and other professional public services.

COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. Considering the restricted and enclosed nature of prisons and closed environments and the prolonged and close contact between individuals, COVID-19 is more likely to have a higher incidence in these settings. This study aims to assess the prevalence of COVID-19 among prisoners.

Papers published in English from 2019 to July 7, 2023, were identified using relevant keywords such as prevalence, COVID-19 and prisoner in the following databases: PubMed/MEDLINE, Scopus and Google Scholar. For the meta-analysis of the prevalence, Cochrane’s Q statistics were calculated. A random effect model was used due to the heterogeneity in COVID-19 prevalence across included studies in the meta-analysis. All analyses were performed in STATA-13.

The pooled data presented a COVID-19 prevalence of 20% [95%CI: 0.13, 0.26] and 24% [95%CI: 0.07, 0.41], respectively, in studies that used PCR and antibody tests. Furthermore, two study designs, cross-sectional and cohort, were used. The results of the meta-analysis showed studies with cross-sectional and cohort designs reported 20% [95%CI: 0.11, 0.29] and 25% [95%CI: 0.13, 0.38], respectively.

Through more meticulous planning, it is feasible to reduce the number of individuals in prison cells, thereby preventing the further spread of COVID-19.