Objective: The knowledge, attitudes, and practices of SUA students about the use of plastics containing endocrine disruptors were investigated in this study. Methodology: A study with 150 participants was conducted to assess individuals' knowledge about endocrine disruptors, attitudes, and plastic use practices. Results: The findings indicate that the participants possessed an average degree of knowledge 50.2 ± 3.85 with the main emphasis of awareness being generic concepts rather than specific substances. Regarding the potential health impacts of endocrine-disrupting chemicals present in plastics, respondents' attitudes ranged from fair to positive, with a mean score of 3.5 ±0.09 indicating a fair attitude overall. Conclusion: It is important to practice polite behavior and increase public awareness of safe plastic disposal methods. Surprising only 38.0% of the participants mentioned that they refrain from heating their food in plastic containers to reduce their exposure to plastics. Students' practices revealed a notable dependence on plastic products despite their awareness of the concerns surrounding endocrine disruptors, as most of them reported using plastic water bottles, plastic cups, and plastic bags almost always. Additionally, only 20.7% of the respondents consistently implemented strategies to prevent exposure to endocrine-disrupting chemicals. Recommendation: The study recommended increasing the use of cleaner plastic substitutes and improving educational programs to convert information into practical actions. Policies that encourage environmentally friendly behavior and raise public awareness of safe plastic disposal techniques should be put into practice.

The integration of LiDAR and Artificial Intelligence (AI) has revolutionized feature detection in urban environments. LiDAR systems, which utilize pulsed laser emissions and reflection measurements, produce detailed 3D maps of urban landscapes. When combined with AI, this data enables accurate identification of urban features such as buildings, green spaces, and infrastructure. This synergy is crucial for enhancing urban development, environmental monitoring, and advancing smart city governance. LiDAR, known for its high-resolution 3D data capture capabilities, paired with AI, particularly deep learning algorithms, facilitates advanced analysis and interpretation of urban areas. This combination supports precise mapping, real-time monitoring, and predictive modeling of urban growth and infrastructure. For instance, AI can process LiDAR data to identify patterns and anomalies, aiding in traffic management, environmental oversight, and infrastructure maintenance. These advancements not only improve urban living conditions but also contribute to sustainable development by optimizing resource use and reducing environmental impacts. Furthermore, AI-enhanced LiDAR is pivotal in advancing autonomous navigation and sophisticated spatial analysis, marking a significant step forward in urban management and evaluation. The reviewed paper highlights the geometric properties of LiDAR data, derived from spatial point positioning, and underscores the effectiveness of machine learning algorithms in object extraction from point clouds. The study also covers concepts related to LiDAR imaging, feature selection methods, and the identification of outliers in LiDAR point clouds. Findings demonstrate that AI algorithms, especially deep learning models, excel in analyzing high-resolution 3D LiDAR data for accurate urban feature identification and classification. These models leverage extensive datasets to detect patterns and anomalies, improving the detection of buildings, roads, vegetation, and other elements. Automating feature extraction with AI minimizes the need for manual analysis, thereby enhancing urban planning and management efficiency. Additionally, AI methods continually improve with more data, leading to increasingly precise feature detection. The results indicate that the pulse emitted by continuous wave LiDAR sensors changes when encountering obstacles, causing discrepancies in measured physical parameters.

This paper investigates the constructability of angles multiples of 3 within the framework of Euclidean geometry. It makes a significant contribution by presenting the first geometric construction for all such angles, offering a rigorous solution to a longstanding geometric problem. The paper reaffirms the efficacy of Euclidean geometry in providing precise constructions and robust proofs for these angles, demonstrating the enduring strength of Euclidean principles from classical to modern times. The presented workflow goes beyond Euclidean geometry to examine non-Euclidean methods, particularly analytical approaches, revealing misconceptions that compromise the genetic and geometric rigor of Euclidean principles. The paper exposes incongruities when algebraic proofs related to angle constructability are applied to the Euclidean system, emphasizing the misalignment of fundamental geometric concepts. A notable result in the paper is the construction of a angle, introducing the “ angle chord” as a novel geometric property. This property challenges assumptions made by non-Euclidean methods and highlights the nuanced geometric properties crucial for rigorous constructions. The paper refutes the fallacy of relying solely on algebra for solutions to angles multiples of , emphasizing the necessity of embracing Euclidean geometry for geometric discoveries. The paper underscores the merits and resilience of Euclidean geometry, showcasing its independence and depth across historical and modern perspectives. The newly presented geometric construction not only resolves a longstanding question but also emphasizes the intrinsic strength and uniqueness of Euclidean principles in contrast to alternative methodologies.

Biodiversity is related to a global problem: its destruction, a fact supported by scientific authorities. It is not trivial that educational dimension has been contemplated as one of the strategies for its conservation. Since 1992 global initiatives such as the Convention on Biological Diversity postulates concepts that linked education and nature conservation. The main objective of this research work is to test the level of assimilation of extracurricular scientific knowledge by primary school pupils. The method chosen for the content was, on the one hand, a master class intervention with an interactive presentation on a digital whiteboard. Third cases were chosen. Each case consisted of a presentation of the current status of a species of fauna present in Spain. On the second part, students were asked to write an essay and to illustrate the experience during the presentation. Regarding the essays, students showed that they were more attracted to the first species that was presented (Iberian lynx) in a proportion of over 45% of cases. The “Endangered species” concept appeared in more than 77% of the texts reviewed. In terms of drawings, almost 55% of the responses seem to devote more attention to the second species described (Testudo graeca). An attempt was made to offer rigorous, structured information related to different aspects of natural reality in order to contemplate the broadest possible vision. The example of an instructional intervention presented here aims to be an alternative to other transmissive teaching models. Likewise, the linking of abstract concepts with socio-cultural reality proved to be a successful strategy to reinforce knowledge about natural biodiversity, endangered species or threat factors.