The study’s purpose is to evaluate the influence of some factors of the model of planned behavior (TPB) and the perceived academic support of the university on the attitude toward entrepreneurship and entrepreneurial intention of students. The results of Structural Equation Modeling (SEM) linear structural model analysis with primary data collected from 1162 students indicated that entrepreneurial intention is influenced by attitude toward entrepreneurship, subjective norm, perceived educational support, and perceived concept development support. In addition, this study also found the positive influence of perceived educational support, concept development support, and business development support on attitude towards entrepreneurship. Interestingly, the influence of perceived business development support on entrepreneurial intention was rejected, and personal innovativeness is demonstrated to promote an attitude toward entrepreneurship. Notably, this study also highlights the moderating role of personal innovativeness on the relationship between attitude toward entrepreneurship and entrepreneurial intention. Based on these findings, several implications were suggested to researchers, universities, and policymakers.

The expanding blue economy, marked by its focus on sustainable use of ocean resources, offers enormous opportunity for Small and Medium-sized Enterprises (SMEs). However, for SMEs to properly integrate and succeed in this economy, they must first have a thorough awareness of the sector’s challenges and prospects. This research used a scoping review and a qualitative study to identify the challenges and opportunities facing SMEs operating in the blue economy. The study discovered recurring themes and gaps in the existing literature by conducting an extensive examination of scholarly publications. The key challenges identified include complicated regulatory frameworks, restricted access to funding, infrastructure restrictions, talent deficiencies, government support, and market outreach. In-depth interviews with Malaysian SME leaders, industry stakeholders, and policymakers were conducted to decipher these findings. The results of interviews confirmed the relevance of the regulatory framework, infrastructure restrictions, talent deficit, and market access challenges in the Malaysian context. In particular, the study revealed emerging opportunities for Malaysian blue SMEs in sectors such as renewable energy, sustainable fisheries, marine biotechnology, and ecotourism. The study emphasizes the importance of an encouraging policy framework, knowledge-sharing platforms, and capacity building activities. It finishes by underlining the ability of SMEs to drive a sustainable and thriving blue economy, if challenges are systematically handled, and opportunities are appropriately capitalized.

In light of swift urbanization and the lack of precise land use maps in urban regions, comprehending land use patterns becomes vital for efficient planning and promoting sustainable development. The objective of this study is to assess the land use pattern in order to catalyze sustainable township development in the study area. The procedure adopted involved acquiring the cadastral layout plan of the study area, scanning, and digitizing it. Additionally, satellite imagery of the area was obtained, and both the cadastral plan and satellite imagery were geo-referenced and digitized using ArcGIS 9.2 software. These processes resulted in reasonable accuracy, with a root mean square (RMS) error of 0.002 inches, surpassing the standard of 0.004 inches. The digitized cadastral plan and satellite imagery were overlaid to produce a layered digital map of the area. A social survey of the area was conducted to identify the specific use of individual plots. Furthermore, a relational database system was created in ArcCatalog to facilitate data management and querying. The research findings demonstrated the approach's effectiveness in enabling queries for the use of any particular plot, making it adaptable to a wide range of inquiries. Notably, the study revealed the diverse purposes for which different plots were utilized, including residential, commercial, educational, and lodging. An essential aspect of land use mapping is identifying areas prone to risks and hazards, such as rising sea levels, flooding, drought, and fire. The research contributes to sustainable township development by pinpointing these vulnerable zones and providing valuable insights for urban planning and risk mitigation strategies. This is a valuable resource for urban planners, policymakers, and stakeholders, enabling them to make informed decisions to optimize land use and promote sustainable development in the study area.

With the development of globalization and diversification, more and more people attach importance to English, and a great number of primary schools in China begin to attach importance to English teaching. As an international mainstream English teaching method, phonics has gradually been used in primary school education in China. Phonics guides students to match letters or letter combinations in the words with sounds, and read or spell words through these pronunciation rules, so that students can learn the vocabulary in a relaxed and pleasant way. It will also reduce obstacles to reading and writing words, and improve students’ learning efficiency. However, there are still some problems in primary school English teaching in China, such as lack of systematic teaching, neglect of phonetic symbol learning and neglect of word meaning, which need to be further improved so that phonics can better assist primary school English teaching.

With the purpose of knowing the phytosocilogy of weeds associated to a carrot crop (Daucus carota L.) under conditions of the municipalities of Ventaquemada and Jenesano-Boyacá, one lot per municipality destined to carrot cultivation was selected and a W-shaped layout was made covering an area of 500 m². Relative density, relative frequency, relative dominance and the importance value index (IVI) were calculated, as well as the Alpha and Beta diversity indices for the sampled areas. A total of 6 families and 11 species were counted, of which 63.64% were represented by annual plants and 36.36% by perennial plants. The class Liliopsida (Monocotyledon) was represented by the Poaceae family. The Magnoliopsida class (Dicotyledon) was represented by the following families: Asteraceae, Brassicaceae, Boraginaceae, Leguminosaceae, Polygonaceae, the last one being the one with the highest number of species. The species R. crispus and P. nepalense were the ones with the highest values of Importance Value Index (IVI) with 0.953 and 0.959, respectively. According to the Shannon-Wiener diversity and Simpson’s dominance indices, the evaluated areas presented a low species diversity and a high probability of dominant species. The results obtained can serve as a basis and tool for carrot growers in the evaluated areas to define management plans for the associated weeds and thus optimize yields in this crop.

This study aims to predict whether university students will make efficient use of Artificial Intelligence (AI) in the coming years, using a statistical analysis that predicts the outcome of a binary dependent variable (in this case, the efficient use of AI). Several independent variables, such as digital skills management or the use of Chat GPT, are considered.The results obtained allow us to know that inefficient use is linked to the lack of digital skills or age, among other factors, whereas Social Sciences students have the least probability of using Chat GPT efficiently, and the youngest students are the ones who make the worst use of AI.