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In this paper, the authors aim to study the effect of hydrogen on the pitting corrosion behavior of Incoloy 825, a commonly used material for heat exchanger tubes in hydrogenated heat exchangers.

The pitting initiation and propagation behaviors were investigated by electrochemical and chemical immersion experiments and observed and analyzed by scanning electron microscope and energy dispersive spectrometer methods.

The results show that hydrogen significantly affects the electrochemical behavior of Incoloy 825; the self-corrosion potential decreased from −197 mV before hydrogen charging to −263 mV, −270 mV and −657 mV after hydrogen charging, and the corrosion current density increased from 0.049 µA/cm² before hydrogen charging to 2.490 µA/cm², 2.560 µA/cm² and 2.780 µA/cm² after hydrogen charging. The pitting susceptibility of the material increases.

Hydrogen is enriched on the precipitate, and the pitting corrosion also initiates at that location. The synergistic effect of hydrogen and precipitate destroys the passive film on the metal surface and promotes pitting initiation.

Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control face a bottleneck problem. The aim of this paper is to design a method to improve the motion performance of musculoskeletal robots in partially observable scenarios, and to leverage the ontology knowledge to enhance the algorithm’s adaptability to musculoskeletal robots that have undergone changes.

A memory and attention-based reinforcement learning method is proposed for musculoskeletal robots with prior knowledge of muscle synergies. First, to deal with partially observed states available to musculoskeletal robots, a memory and attention-based network architecture is proposed for inferring more sufficient and intrinsic states. Second, inspired by muscle synergy hypothesis in neuroscience, prior knowledge of a musculoskeletal robot’s muscle synergies is embedded in network structure and reward shaping.

Based on systematic validation, it is found that the proposed method demonstrates superiority over the traditional twin delayed deep deterministic policy gradients (TD3) algorithm. A musculoskeletal robot with highly redundant, nonlinear muscles is adopted to implement goal-directed tasks. In the case of 21-dimensional states, the learning efficiency and accuracy are significantly improved compared with the traditional TD3 algorithm; in the case of 13-dimensional states without velocities and information from the end effector, the traditional TD3 is unable to complete the reaching tasks, while the proposed method breaks through this bottleneck problem.

In this paper, a novel memory and attention-based reinforcement learning method with prior knowledge of muscle synergies is proposed for musculoskeletal robots to deal with partially observable scenarios. Compared with the existing methods, the proposed method effectively improves the performance. Furthermore, this paper promotes the fusion of neuroscience and robotics.

This chapter on anti-racism struggles applies an anti-racist activist framing, both critically examining and recognising the milestones achieved through centuries of pro-justice and anti-racism struggles. It delves into the arduous journey that the global fight for racial equity has undergone and highlights the significant progress as well as setbacks experienced during this lengthy struggle. The earliest history of the fight against racial oppression and domination goes back to anti-slavery and anti-colonial movements. Scholars have analysed the emergence, development and state of global anti-racism struggles in a variety of ways. I approach this subject from a sociological perspective, highlighting the role of social structures, groups and institutions that have contributed to shaping the outcomes of anti-racist initiatives. While recognising the role of individuals and leading political activists, this chapter emphasises anti-racism as a collective social justice struggle. To do this, I explore various local and global anti-racism endeavours and examine how they may influence discussions on race, racism and racial equity and their evolving trajectories across different societies.

The purpose of this study is to examine the relationship between pollutant emissions, financial development and IFRS in developed and developing countries between 1998 and 2022.

Data were obtained from World Development Indicators and World Governance Indicators of the World Bank.

Using FGLS and GMM estimators, the results provide evidence that financial development has a significant positive impact on a variety of pollutant emissions. However, this positive impact is moderated by IFRS for the overall sample and country income groups.

Governments and regulatory organizations should support companies’ investments in clean energy and technologies to slow down environmental degradation. Tax credits and subsidies may be helpful to achieve this goal. Also, governments may encourage companies to cooperate with universities and research institutions to develop environment-friendly production and distribution methods to reduce pollution. Although stakeholders may obtain information about environmental issues in financial statements that are prepared in accordance with IFRS, there is a need for standardization of their contents.

Greenhouse gases are major contributors to climate change and global warming. In addition to private costs borne by producers, the production and consumption of products have social costs arising from pollution that affects air, water, and soil. Pollution adversely affects people's physiological and psychological health, which decreases labor productivity, thereby leading to a decrease in economic growth.

According to the author’s knowledge, this is the first study that examines the impact of IFRS on the relationship between financial development and pollutant emissions.

The COVID-19 pandemic has created a significant disruption in the educational systems worldwide. Some institutions opted for emergency remote education due to the need to cancel in-person activities. The aims of this paper were to evaluate the use of asynchronous methodology in health sciences education, determine whether asynchronous methodology was sacrificing overall student satisfaction, and investigate whether satisfaction improved as the program develops.

Initially, there was phase 1 that corresponded to four weeks of activities. Each professor produced a video lesson, and after each video lesson, a weekly educational activity was made available. Next, phase 2 was implemented using the same methodology, however lasting six weeks. Three questionnaires were developed, and a Likert scale was administered to verify the students’ level of satisfaction. Data were analyzed using frequency distributions, mean values, standard deviation and confidence interval. The normality of the sum data (total of the questionnaires) was tested using the Kolmogorov–Smirnov test.

Although the students pointed out that the asynchronous methodology facilitated access to the content and considered this methodology satisfactory, they expressed a reduced level of satisfaction regarding emergency remote education in general when data from the first weeks were compared to those of the previous weeks. It is clear that students became increasingly discouraged and tired over time, which motivated the institution to shift into a combination of synchronous and asynchronous methodology to improve student learning.

Teaching in the field of health care encompasses difficult competencies that sometimes are impossible to be learned remotely, so there is a need to examine and evaluate properly the remote education in this area. With careful planning, educational institutions can evaluate their experiences during the pandemic, allowing those involved to highlight strengths and identify weaknesses to better prepare for future needs to improve remote education.