The history of organic polymers is a remarkable journey from the discovery of natural materials like rubber and silk to the development of sophisticated synthetic polymers that have transformed industries and modern life. This comprehensive review article presents a detailed account of the evolution of organic polymers. It begins with the early uses of natural polymers and explores key breakthroughs, including the invention of Bakelite, nylon, and neoprene. The theoretical foundations of polymer science, laid by Hermann Staudinger, are discussed, and the post-war surge in polymer development is examined, including the introduction of polyethylene, polypropylene, and PVC. Notable advances in polymer chemistry, such as isotactic polypropylene and silicone polymers, are highlighted. The article also delves into the development of high-performance polymers like Kevlar and carbon-based materials, offering insights into their applications. Moreover, it discusses the current trends in polymer science, emphasizing sustainability and biodegradability. As the world continues to rely on polymers for numerous applications, this review provides a historical perspective and a glimpse into the future of organic polymers, where innovations are expected to shape various aspects of technology, healthcare, and environmental protection.

The central government of China has intensively guided regional integration and policy coordination towards the development of digital governance in the last ten years. The Guangdong-Hong Kong-Macao Greater Bay was one of the most important regions of China expected to accelerate regional development through policy coordination and establishment of digital infrastructures. This article adopted the method of content analysis to explore the policy transitions of digital governance in the Greater Bay including policy contents (in terms of policy objectives and instruments) and policy networks. Based on our empirical analysis, we found that top-down guidance from the central government did not necessarily generate regional coordination. Different governments of the same region could start policy coordination from shared policy objectives and policy instruments and establish innovative governance frameworks to achieve consensus. Therefore, regional coordination could be fulfilled.

Cucumber (Cucumis sativus L.) is a tropical vegetable and a source of vitamins such as K, C, and B. It is commonly grown and sold for daily consumption, but picking the right fruit size is more profitable. Therefore, a method for estimating the fruit weight is highly recommended. This paper aimed to determine the dimensions of cucumber fruit based on its usual harvesting size and to establish a model to show the relationship between fruit weight, fruit length, and fruit diameter. Cucumber was planted in the experimental field belonging to the Faculty of Agricultural Biosystems Engineering, Royal University of Agriculture, Phnom Penh, Cambodia, from January to June 2022. In the study, 48 market-size fruits were randomly selected from the plots to measure their weight, length, and diameter. The result shows that fruit length and fruit diameter had a positive relationship (P < 0.001; R = 0.70). Fruit weight was 3.38 fruit length × fruit diameter (P <0.001; R = 0.95). Nevertheless, L/D ratio negatively affected fruit weight, when it exceeded 3:1. Fruit weight was greater than 100 g when fruit diameter was over 4 cm and fruit length was over 10 cm. Therefore, when picking cucumber fruits, one must consider fruit length and diameter to be profitable. Further studies will focus on measuring cucumber fruit already available on the market to understand more about actual consumer preferences.

The purpose of this study is to look at the negative environmental impacts and social problems, which require a government response to maintain the sustainability of the palm oil industry. This research uses Online Research Methods (ORMs) to collect data and information through the internet and other digital technologies. The collected data was then coded using Nvivo 12 Plus. The purpose of this study is to fill the research void left by previous researchers by analyzing investment strategies and services in supporting the sustainability of the palm oil industry in Riau Province. This study shows that to support the potential of the palm oil industry to remain optimal, the central and local governments coordinate to provide investment services and pay attention to the sustainability issues of the palm oil industry. Some important aspects to consider are strengthening regulations, an integrated plantation licensing system, improving access to markets, RSPO certification, realization of foreign investment, downstream industry, replanting programme, plantation revitalisation programme, and sustainable plantation partnerships. However, there are still some crucial challenges, particularly land conflicts, climate change, environmental issues, limited technology and innovation, and export market dependence. These challenges may hamper future investment opportunities.

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%.