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Kelp forests are essential marine ecosystems increasingly compromised by human activities. Effective reforestation strategies are urgently needed, and the "green gravel" method is a viable tool already used in some European regions. This study aimed to assess the success of this method using the native Kelp species Laminaria ochroleuca on the Portuguese coastline. Cultures of green gravel were reared until the specimens reached a size of approximately 3 cm. The gravel was then deployed at selected sites in Peniche, Berlengas, and Cascais. Over an eight-month period, scientific scuba divers monitored the integration of Kelp, along with associated fish, invertebrate, and algae communities. Nutrient availability, temperature, water movement, substrate type, and Rugosity Index (RI) were also measured. The highest success rate was 12% in Consolação, with Elefante and Galos (Berlengas) reaching 7% and 4%, respectively. By the end of the monitoring period, Cascais had no remaining Kelp on green gravel. Present data suggest that higher success is dependent on less rugged and higher RI topography. Higher grazing pressure, rougher terrain, and unexpected sedimentation appear to be the main obstacles to deployment success. Solid knowledge (biologic and topographic) on the restoration site, starting restoration actions near already established Kelp forests, and significantly scaling up restoration efforts could substantially improve the success of the green gravel method in future reforestation campaigns. [ABSTRACT FROM AUTHOR]

Marine-derived nutrients and bioactive compounds may offer a myriad of biological benefits, such as anticancer and anti-inflammatory properties, and technological potential, enhancing food quality as additives. Their role in the sustainable development of food technology is fundamental, especially in advancing the knowledge of functional foods and related technologies. Algae are considered one of the major sources of marine-derived ingredients and the subject of several recent studies. Despite their potential, the translation of marine ingredients' potential into a marine-based competitiveness of the food industry faces hurdles in the extraction process and operational systems scale-up that the industry needs to tackle. The complexity of marine matrices with diverse compounds and solubilities adds complexity to extraction processes and may lead to low yields or bioactivity loss. Contaminants, like heavy metals and pesticide residues in marine organisms, require rigorous purification processes for product safety. The use of biorefinery systems in marine-based ingredients' production, particularly cascade processes, offers zero-waste solutions, contributing to the blue economy and aligning with UN sustainability goals. Sustainability assessment tools are critical for evaluating marine-based food production's environmental, social, and economic impacts. A continued exploration and collaboration are essential for the future, fostering innovation and sustainability to create a resilient, equitable, and eco-friendly food system. [ABSTRACT FROM AUTHOR]

The traditional approach of single-word brand names faces constraints due to trademarks, prompting a shift towards fusing two or more words to craft unique and memorable brands, exemplified by brands such as SalesForce© or SnapChat©. Furthermore, brands such as Kodak©, Xerox©, Google©, Häagen-Dazs©, and Twitter© have become everyday names although they are not real words, underscoring the importance of brandability in the naming process. However, manual evaluation of the vast number of possible combinations poses challenges. Artificial intelligence (AI), particularly natural language processing (NLP), is emerging as a promising solution to address this complexity. Existing online brand name generators often lack the sophistication to comprehensively analyze meaning, sentiment, and semantics, creating an opportunity for AI-driven models to fill this void. In this context, the present document reviews AI, NLP, and text-to-speech tools that might be useful in innovating the brand name generation and evaluation process. A systematic search on Google Scholar, IEEE Xplore, and ScienceDirect was conducted to identify works that could assist in generating and evaluating brand names. This review explores techniques and datasets used to train AI models as well as strategies for leveraging objective data to validate the brandability of generated names. Emotional and semantic aspects of brand names, which are often overlooked in traditional approaches, are discussed as well. A list with more than 75 pivotal datasets is presented. As a result, this review provides an understanding of the potential applications of AI, NLP, and affective computing in brand name generation and evaluation, offering valuable insights for entrepreneurs and researchers alike. [ABSTRACT FROM AUTHOR]