This paper aims to investigate local communities’ participation in eco-tourism projects by using the community of Situ Cisanti located in Tarumajaya Village, West Java as a case. Data were gathered through observation, in-depth interviews, and documentation analysis. Observations and in-depth interviews were conducted simultaneously for two months, from September to October 2021. In-depth interviews were conducted with 15 informants from the elements; village government officials of Tarumajaya, Perhutani, and local communities who participated in the Situ Cisanti eco-tourism project, which was completed through a documents analysis. According to the findings, local community participation in Situ Cisanti eco-tourism consists of conservation and economic participation. Conservation participation is demonstrated by their participation in restoration and greening activities such as reforestation, etc. in Situ Cisanti and its surroundings, whereas economic participation is demonstrated by the establishment of stalls, culinary, coffee, souvenir, and homestay businesses as a result of Situ Cisanti eco-tourism. Furthermore, the existence of this eco-tourism has empowered women because new business opportunities that arise are not only run by men but also by women. As a result, this study implies that the participation of local eco-tourism communities not only has an impact on empowering conservation knowledge and economics, but it can also imply women empowerment.

Under the background of green economic transformation, the sustainable utilization of ecological resources has become a trend, and bamboo all-for-one tourism has become a new development direction for bamboo-resource-rich areas. Based on the all-for-one tourism model and characteristics of bamboo resources, this paper puts forward a bamboo all-for-one tourism model, which shows the relationship between resources, products, and markets, and elaborates on the joint effect mechanism of industrial environment, governance environment, and external environment. Taking Yibin City, Sichuan Province as an example, this paper also analyzes existing problems of developing bamboo all-for-one tourism and then proposes suggestions to provide effective analytical ideas and reference, such as establishing a market-oriented all-product development model, introducing the sustainable development concept of bamboo management, establishing the management concept of sharing by all people, and driving all industries developing in a coordinated way.

In this study, robust and defect-free thin film composite (TFC) forward osmosis (FO) membranes have been successfully fabricated using ceramic hollow fibers as the substrate. Polydopamine (PDA) coating under controlled conditions is effective in reducing the surface pores of the substrate and making the substrate smooth enough for interfacial polymerization. The pure water permeability (A), solute permeability (B), and structural parameter (S) of the resultant FO membrane are 0.854 L·m^–2·h⁻¹·bar⁻¹ (LMH/Bar), 0.186 L·m^–2·h⁻¹ (LMH), and 1720 µm, respectively. The water flux and reverse draw solute flux are measured using NaCl and proprietary ferric sodium citrate (FeNaCA) draw solutions at low and high osmotic pressure ranges. As the osmotic pressure increases, a higher water flux is obtained, but its increase is not directly proportional to the increase in the osmotic pressure. At the membrane surface, the effect of dilutive concentration polarization is much less serious for FeNaCA-draw solutions. At an osmotic pressure of 89.6 bar, the developed TFC membrane generates water fluxes of 11.5 and 30.0 LMH using NaCl and synthesized FeNaCA draw solutions. The corresponding reverse draw solute flux is 7.0 g·m^–2·h⁻¹ (gMH) for NaCl draw solution, but it is not detectable for FeNaCA draw solution. This means that the developed TFC FO membranes are defect-free and their surface pores are at the molecular level. The performance of the developed TFC FO membranes is also demonstrated for the enrichment of BSA protein.

The cost of diagnostic errors has been high in the developed world economics according to a number of recent studies and continues to rise. Up till now, a common process of performing image diagnostics for a growing number of conditions has been examination by a single human specialist (i.e., single-channel recognition and classification decision system). Such a system has natural limitations of unmitigated error that can be detected only much later in the treatment cycle, as well as resource intensity and poor ability to scale to the rising demand. At the same time Machine Intelligence (ML, AI) systems, specifically those including deep neural network and large visual domain models have made significant progress in the field of general image recognition, in many instances achieving the level of an average human and in a growing number of cases, a human specialist in the effectiveness of image recognition tasks. The objectives of the AI in Medicine (AIM) program were set to leverage the opportunities and advantages of the rapidly evolving Artificial Intelligence technology to achieve real and measurable gains in public healthcare, in quality, access, public confidence and cost efficiency. The proposal for a collaborative AI-human image diagnostics system falls directly into the scope of this program.