This study examines conditions that impact PPP delivery success or failure in the roadways sector in India using Qualitative Comparative Analysis. QCA is well-suited for problems where multiple factors combine to create pathways leading to an outcome. Past investigations have compared PPP and non-PPP project delivery performance, but this study examines performance within PPPs by uncovering a set of conditions that combine to influence the success or failure road PPP project delivery in India. Based on data from 21 cases, pathways explaining project delivery success or failure were identified. Specifically, PPPs with high concessionaire equity investment and low regional industrial activity led to project delivery success. Projects with lower concessionaire equity investment and low reliance on toll revenue and with either: (a) high project technical complexity or (b) high regional industrial activity, led to project delivery failure. The pathways identified did not have coverage values that they were extremely strong. Coverage strength was hindered by lack of access to information on additional conditions that could be configurationally important. Further, certain characteristics of the Indian market limit generalization. Identification of combinations of conditions leading to PPP project delivery success or failure improves knowledge of the impacts of structure and characteristics of these complex arrangements. This study is one of the first to use fuzzy QCA to understand project delivery success/failure in road PPP projects. Moreover, this study takes into account factors specific to a sector and delivery mode to explain project delivery performance.

Cases of human trafficking are becoming more prevalent and represent grave abuses of human rights. Both locally and internationally, victims of human trafficking run the danger of being exploited, violent, or infected with contagious illnesses. The Indonesian government has not fully complied with the minimal criteria for safeguarding victims of human trafficking, notwithstanding Law Number 21 of 2007 for the Eradication of the Crime of Human Trafficking. Human rights restoration and respect for victims of human trafficking must be given priority in the implementation of legal protection for these individuals. To strengthen and increase the security of victims’ rights in the future, this study intends to conduct a thorough analysis of the humanism approach model and policies for safeguarding victims of human trafficking. This research uses an empirical technique to support its normative legal analysis. Primary and secondary legal sources are used in this research. The study’s findings show that the protection provided by humanist criminal law for victims of human trafficking is founded on humanitarian principles that derive from the divine principles found in the Pancasila ideology. There are additional requirements for punishment, such as its purpose, its ability to serve as therapy, and its determination to reflect the victim’s and society’s sense of justice. This criminal law is founded on the principles of legality and balance.

Monitoring marine biodiversity is a challenge in some vulnerable and difficult-to-access habitats, such as underwater caves. Underwater caves are a great focus of biodiversity, concentrating a large number of species in their environment. However, most of the sessile species that live on the rocky walls are very vulnerable, and they are often threatened by different pressures. The use of these spaces as a destination for recreational divers can cause different impacts on the benthic habitat. In this work, we propose a methodology based on video recordings of cave walls and image analysis with deep learning algorithms to estimate the spatial density of structuring species in a study area. We propose a combination of automatic frame overlap detection, estimation of the actual extent of surface cover, and semantic segmentation of the main 10 species of corals and sponges to obtain species density maps. These maps can be the data source for monitoring biodiversity over time. In this paper, we analyzed the performance of three different semantic segmentation algorithms and backbones for this task and found that the Mask R-CNN model with the Xception101 backbone achieves the best accuracy, with an average segmentation accuracy of 82%.

The China-Pakistan Economic Corridor (CPEC) has been one of the most prominent components of the Belt and Road Initiative (BRI). Most of the discussion on CPEC has centered around the macroeconomic effects on the economy. However, research on the fine details of CPEC’s financing structure has not been conducted. This paper aims to fill the gap by providing a detailed description of the financing of CPEC and how the money maps on to different sectors of the Pakistani economy. We also discuss some macroeconomic concerns and ways to mitigate these risks.

The use of different energy sources and the worry of running out of some of them in the modern world have made factors such as environmental pollution and even energy sustainability vital. Vital resources for humanity include water, environment, food, and energy. As a result, building strong trust in these resources is crucial because of their interconnected nature. Sustainability in security of energy, water and food, generally decreases costs and improves durability. This study introduces and describes the components of a system named “Desktop Energetic Dark Greenhouse” in the context of the quadruple nexus of water, environment, food, and energy in urban life. This solution can concurrently serve to strengthen the sustainable security of water, environment, food, and energy. For home productivity, a small-scale version of this project was completed. The costs and revenues for this system have been determined after conducting an economic study from the viewpoints of the investor and the average household. The findings indicate that the capital return period is around five years from the investor’s perspective. The capital return on investment for this system is less than 4 years from the standpoint of the households. According to the estimates, this system annually supplies about 20 kg of vegetables or herbs, which means about one third of the annual needs of a family.

State support for agriculture is a crucial tool for adjusting the competitive advantages of agricultural producers to a volatile market environment. In countries with diverse natural conditions for agriculture, however, the allocation of subsidies often focuses on bridging spatial development gaps rather than maximizing the return on inputs. To improve the efficiency of resource use in agriculture, it is essential to tailor subsidy criteria to regional disparities in agricultural potential. Using the example of Russia’s 81 administrative regions, the authors have tested a five-stage methodology for determining the support-generated parameters of output, efficiency, impact, revenue, and profitability. This methodology takes into account both natural and economic factors that contribute to the competitive advantages of each region. The study aims to identify the parts of the performance indicators, such as gross agricultural output and revenue, that are influenced by the amount of subsidies in five different types of territories, which are categorized by the cadastral value of their farmland. It has been found that the allocation of subsidies is not entirely based on the return on the funds allocated. There is a discrepancy between the competitive advantages of these territories in agricultural production and the amount of funds they receive through government support programs. The efficiency of government support differs significantly depending on the type of agricultural product produced in each territory. The approach developed by the authors provides a tool that policy makers can use when tuning the allocation of subsidies based on the differences in the agricultural potential of each territory.