Manual scavenging refers to the practice of manually cleaning, carrying, disposing or handling human excreta from dry latrines and sewers. It is one of the most dehumanizing and deplorable practices that violate basic human rights and dignity. This practice is linked to India’s caste system where so-called lower castes are expected to perform this job. Despite being outlawed in 1993, manual scavenging continues to exist in India due to socio-economic discrimination and lack of rehabilitation of manual scavengers. This paper attempts to provide an in-depth understanding. The harsh realities by qualitative systemic review of manual scavenging in India and how it negatively impacts human rights. It reviews relevant literature on the prevalence, causes, adverse effects, and laws against manual scavenging. The results indicate that manual scavenging is still practiced across many states in India. Manual scavengers face grave health hazards and socio-economic hardships. The laws against manual scavenging have failed to abolish this practice due to administrative apathy, lack of rehabilitation support for liberated scavengers, and continued prevalence of dry latrines necessitating manual disposal of excreta. The paper emphasizes the need for more concerted efforts by the government and civil society to end manual scavenging to uphold human rights, dignity, and justice for all. There is an urgent need for extensive awareness campaigns, social support, and proper rehabilitation of liberated scavengers into alternative professions.

Developing “New Quality Productive Forces” (NQPFs) has been accepted as a new theory to accelerate the high-quality development in China. In current, China’s high-quality development mainly relies on the traction of the digital economy. In view of this, developing NQPFs in China’s digital economy sector requires locate and remove some obstacles, such as the insufficient utilization of data, inadequate algorithm regulation, the mismatched supply and demand of regional computing power and the immature market environment. As a solution, it is necessary to allocating data property rights in a market-oriented way, establishing a user-centered algorithm governance system, accelerating the establishment of the national integrated computing network, and maintaining fair competition to optimize the market environment.

The paper examines the motivations, financing, expansion and challenges of the Belt and Road Initiative (BRI). The BRI was initially designed to address China’s overcapacity and promote economic growth in both China and in countries along the “Belt” and “Road” through infrastructure investment and industrial capacity cooperation. It took into account China’s strategic transition in its opening-up policy and foreign policy to pay more attention to the neighboring countries in Southeast Asia and Central and West Asia when facing greater strategic pressure from the United States in East Asia and the Pacific region. More themes have been added to the initiative’s original framework since its inception in 2013, including the vision of the BRI as China’s major solution to improve international economic cooperation and practice to build a “community of shared future for mankind”, and the idea of the Green Silk Road and the Digital Silk Road. Chinese state-owned enterprises and policy and commercial banks have dominated investment and financing for BRI projects, which explains the root of the problems and risks facing the initiative, such as unsustainable debt, non-transparency, corruption and low economic efficiency. Measures taken by China to tackle these problems, for example, mitigating the debt distress and improving debt sustainability, are unlikely to make a big difference anytime soon due to the tenacity of China’s long-held state-driven investment model.

Countering cyber extremism is a crucial challenge in the digital age. Social media algorithms, if designed and used properly, have the potential to be a powerful tool in this fight, development of technological solutions that can make social networks a safer and healthier space for all users. this study mainly aims to provide a comprehensive view of the role played by the algorithms of social networking sites in countering electronic extremism, and clarifying the expected ease of use by programmers in limiting the dissemination of extremist data. Additionally, to analyzing the intended benefit in controlling and organizing digital content for users from all societal groups. Through the systematic review tool, a variety of previous literature related to the applications of algorithms in the field of online radicalization reduction was evaluated. Algorithms use machine learning and analysis of text and images to detect content that may be harmful, hateful, or call for violence. Posts, comments, photos and videos are analyzed to detect any signs of extremism. Algorithms also contribute to enhancing content that promotes positive values, tolerance and understanding between individuals, which reduces the impact of extremist content. Algorithms are also constantly updated to be able to discover new methods used by extremists to spread their ideas and avoid detection. The results indicate that it is possible to make the most of these algorithms and use them to enhance electronic security and reduce digital threats.

Lack of knowledge, attitude, and behavior in managing leftover foods in households impacts the natural ecosystem and food chain, particularly in developing countries. This research aims to analyze appropriate methods for reducing and processing food waste produced in household areas. This research method uses qualitative research with operational research methods carried out for 6 months on 25 housewives in Pondok Labu Village in South Jakarta, Indonesia. The research was carried out in 3 stages, the first stage before the intervention, the second stage providing the intervention, and the third stage after the intervention. Results showed that before the intervention, on average each respondent produced 351 g of food waste each day. This amount decreased to 8.43 g/day after respondents participated in socialization to reduce food waste and training to manage food waste. The concluded that a combination of education and training improves knowledge, attitude, and behavior in household food waste management and helps moderate food waste generation.

The application of quality management methods and tools is an important prerequisite for the success and performance increase of manufacturing enterprises. The paper deals with the application of methods and tools of quality management (MTQM) in manufacturing enterprises. The paper aims to analyze whether there is a relationship between the application of MTQM and the size of enterprises, the use of MTQM, and the performance of enterprises measured through the achieved profit. It also analyzes the impact of MTQM on the agility of manufacturing enterprises measured through the decrease in sales expressed in revenues during the pandemic period. The paper presents the results of the research which was conducted between 2020–2022. Several statistical tools such as the Chi-square goodness-of-fit test, Pearson’s chi-square test, and contingency analysis were used to evaluate the different analyses as well as the representativeness of the sample. Based on the results, it can be concluded that there are differences in the use of MTQM and the size of the enterprise as well as the performance of the enterprises. At the same time, the hypothesis that enterprises using a wider range of quality management methods and tools have a higher potential to adapt to unexpected market changes was also confirmed.