This paper aims to explain the administrative and the Environmental, Social and Governance (ESG) of the Indonesian Spaceport Project in Biak, Papua, Indonesia, under the Public-Private Partnerships (PPP) scheme, particularly from the protest to fear of environmental damage and traditional rights. This paper analyzes the factors that cause the local society’s reluctance to accept the development of Indonesia’s very first commercial spaceport. This paper uses a doctrinal methodology, which examines changes in the trend of ESG in implementing PPP projects. The method used is a qualitative systematic review of national and international studies. This paper finds that the lack of legal certainty for administrative and ESG as the main factor contributing to the pitfall of the PPP project in Biak Papua. No clear Government Contracting Agency (GCA), plus the fact that the Indonesian government puts too much weight on business consideration in PPP while Papuan people need more ESG, especially considering the historical conflict in the region, has been the epicenter of the problem. Given the ESG-PPP regulatory failure of spaceport development in Biak, more focused studies using comparative study methodology are needed to propose a more robust and customized ESG in PPP regulations in a politically and historically sensitive area. The authors forward a regulatory reform to balance administration, ESG, and business considerations in PPP projects for a spaceport.

The impact of human activities on the quality of urban environment has become increasingly prominent and urban soil pollution problems on the health of local residents also gradually prominent. In addition, the study of heavy metal pollution in urban surface soil is an important part of the evolution model of urban geological environment so it is necessary to analyze the heavy metal pollution in urban soil. In this paper, the data of the given samples are processed and analyzed by MATLAB software and EXCEL spreadsheet. The three - dimensional image model and the planar model of metal element space are established by interpolation method. The spatial distribution of eight kinds of heavy metal elements in the city is presented in detail. For the urban environment, especially the macro-grasp of soil pollution, regulation provides a simple and accurate three-dimensional spatial distribution model of pollutants. Combined with data analysis of the urban area of different areas of heavy metal pollution to make a preliminary judgment. The data show that in the five types of cities, heavy soil pollution is the most serious in industrial areas. A method of imagination of the data analysis is boldly used and then combined with the distribution map, they found a source of pollution. For the spatial distribution of heavy metal elements, this paper uses EXCEL to calculate the data and MATLAB to map the data which showed a detailed and intuitive distribution map according to the distribution map can be analyzed in different areas of pollution; For the second question, this paper uses a method of design to deal with the data, part of the data for the results of the more effective show to determine the cause of pollution. For the third question, this article will be more serious pollution or a wider range of local screening, analysis, and then speculate the location of pollution sources. For other pollution information, this article is based on the modeling process encountered in the thought of the factors given.

Intra-regional trade serves as a key growth engine for East Asian economies. Accompanying the rapid growth of bilateral and intra-regional trade ties, the East Asian economies are becoming increasingly connected and interdependent. Infrastructure connectivity plays a crucial role in bridging different areas of the East Asian region and enabling them to reap the full socioeconomic benefits of economic cooperation and integration. Nevertheless, further improvement of infrastructure in the region faces major challenges due to the lack of effective mechanisms for coordination and dialogue on regional integration through funding infrastructure projects, as well as the serious trust deficit among member states that has arisen from the on-going territorial and historical disputes.

This research implements sustainable environmental practices by repurposing post-industrial plastic waste as an alternative material for non-conventional construction systems. Focusing on the development of a recycled polymer matrix, the study produces panels suitable for masonry applications based on tensile and compressive stress performance. The project, conducted in Portoviejo and Medellín, comprises three phases combining bibliographic and experimental research. Low-density polyethylene (LDPE), high-density polyethylene (HDPE), and polypropylene (PP) were processed under controlled temperatures to form a composite matrix. This material demonstrates versatile applications upon cooling—including planks, blocks, caps, signage, and furniture (e.g., chairs). Key findings indicate optimal performance of the recycled thermoplastic polymer matrix at a 1:1:1 ratio of LDPE, HDPE, and PP, exhibiting 15% deformation. The proposed implementation features 50 × 10 × 7 cm panels designed with tongue-and-groove joints. When assembled into larger plates, these panels function effectively as masonry for housing construction, wall cladding, or lightweight fill material for slab relieving.

Maps of forest stand condition—the current phase of the forest-forming process—will be useful for foresters in their forest management in addition to the forest planning and cartographic materials. The mapping methodology was applied in the test area of the Bolshemurtinsky forest district of the Krasnoyarsk region, which is typical for the southern taiga forests of East Siberia. Source data for mapping was obtained on the basis of descriptions of the forest subcompartments on the GIS attribute table of the forest district. Forest stand confinement to the terrain relief indicators was identified on the basis of the SRTM 55-01 digital terrain model data. Spatial analysis has been performed using the ArcGIS Spatial Analyst module. Mapping capability has been shown not only for the year of forest inventory but also for the earlier period of time. To determine the predominant species and the age of the 100-year-old forest stand, a scheme was proposed in which the conceivable options are typified depending on the succession trend, the forest stand age prior to disturbance, and the period of reforestation. Map fragments of the test area as of 2006—the year of forest inventory—and as of 1906—the year of the intensive colonization beginning in southern Siberia—are demonstrated. Maps of forest condition in the test area represent successions that are typical in the southern taiga forests of Siberia: post-harvest, pyrogenic, and biogenic. The methodology of forest condition mapping is universal.

In view of the fact that the convolution neural network segmentation method lacks to capture the global dependency of infected areas in COVID-19 images, which is not conducive to the complete segmentation of scattered lesion areas, this paper proposes a COVID-19 lesion segmentation method UniUNet based on UniFormer with its strong ability to capture global dependency. Firstly, a U-shaped encoder-decoder structure based on UniFormer is designed, which can enhance the cooperation ability of local and global relations. Secondly, Swin spatial pyramid pooling module is introduced to compensate the influence of spatial resolution reduction in the encoder process and generate multi-scale representation. Multi-scale attention gate is introduced at the skip connection to suppress redundant features and enhance important features. Experiment results show that, compared with the other four methods, the proposed model achieves better results in Dice, loU and Recall on COVID-19-CT-Seg and CC-CCIII dataset, and achieves a more complete segmentation of the lesion area.