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.

The Douala-Edea National Park is a coastal protected area that opens to the Atlantic Ocean, and contains an abundant wildlife which finds a privilege habitat there, and certain taxa such as epiphytes, which are of particular interest for conservation. In many tropical forests, vascular epiphytes are one of the richest taxa, with major impacts on the nutrient and hydrological cycles. The aim of this research was to study the effect of the disturbance of habitat on the floristic composition of vascular epiphytes in the Douala-Edea National Park. This study was carried out between January - April 2021 in three types of disturbed habitats at the northern part of the park. Three plots of 100 m × 100 m dimensions were laid out across three ecosystems along the Sanaga river. The sampling method consisted in the direct observation of five adjacent transects of 100 m x 20 m dimensions inside each plot. Epiphytes species were evaluated on all trees of DBH ≥10 cm. Epiphytes' life-forms and the position on the host trees occupied by the epiphytes were also recorded. A total of 18 species belonging to 16 genera and 13 families were identified. Culcasia sp. was the most common species with a relative frequency of 30.27%. Biological indicators were represented by Ferns, with four species, and Orchidaceae, with one species. The epiphytes species richness was highest in the low disturbed habitat (13 species), and lowest in the highly disturbed habitat (8 species). Strict epiphytes were highly recorded in the low disturbed habitat (6 species), and were absent in the highly disturbed habitat. Hemi-epiphytes were the commonest life-form (12 species) in the highly disturbed habitat, and have been defined as indicators of the perturbation of the habitat. Canopy was mostly sollicitated by epiphytes in the low disturbed habitat (66.25%) than the moderate disturbed habitat (49.85%), and highly disturbed habitat (30.66%). It has been found that the different forest sites have an influence on the typology of epiphytic species, and therefore, epiphytic flora should be managed for the conservation of the biodiversity in tropical forests.

Background: The COVID-19 pandemic disrupted routine osteoporosis care due to clinic closures and limited in-person consultations. Telehealth emerged as an alternative model enabling remote care delivery and monitoring. However, previous reviews on telehealth either did not include the pandemic period or had a limited focus in scope. Evidence synthesized specifically for osteoporosis care during the pandemic is needed but lacking. Methods: We systematically searched PubMed, MEDLINE, EMBASE, PsycINFO, Web of Science, and CINAHL for studies on telehealth for osteoporosis published between January 2021 and March 2023. Five studies met the inclusion criteria of: osteoporosis population, telehealth intervention, and COVID-19 pandemic timeframe. Data was extracted on study characteristics, COVID-19 outcomes, osteoporosis status, telehealth purpose, patient satisfaction, and clinical outcomes. Result: The five studies showed telehealth was used for monitoring data, delivering test results, adjusting medications, and assessments. Osteoporosis prevalence among telehealth users ranged 30-100%. High patient satisfaction was reported with telehealth versus in-person care. No major differences occurred in medication delays or fractures between telehealth and in-person groups. Conclusion: This review found telehealth enables effective osteoporosis care and monitoring during the pandemic, with high patient and provider satisfaction. However, more robust randomized controlled trials are needed to establish stronger evidence around telehealth's impacts on clinical osteoporosis outcomes. Implications: Though promising, further high-quality studies will help clarify telehealth's role in improving osteoporosis care and outcomes. Findings inform guidelines on integrating telehealth into routine management. Evidence on user perspectives optimizes telehealth implementation policies.

There have been various concerns about the environmental impact of construction works. This generates a need to take a more proactive approach in evaluating the environmental impacts of construction operations and further explore ways to reduce the environmental impacts. Enormous opportunities exist within the building industry to achieve a reduction in greenhouse gas emissions. The aim of the study is to develop a framework for the evaluation of improvement opportunities for environmental impact for onsite and offsite building construction works using life cycle assessment (LCA) and value-stream-mapping concepts. Various tools for LCA exist; however, there is a need for the development of an LCA framework and improvement opportunities that can be localized to various communities to evaluate improvement opportunities for building construction. This study conducts a review of methods to evaluate the LCA of buildings on local construction sites. A procedure for establishing improvement opportunities is also developed. Based on the author’s knowledge and experience, including site visits, using value stream mapping (VSM) techniques, a conceptual framework of the present state map and future state map of residential construction works was developed. The study presents a procedure for the evaluation of improvement opportunities for the environmental impacts of construction operations.

The decision to choose between onsite and offsite construction is important in the effort toward sustainable construction. Offsite construction is often promoted as an environmentally friendly approach to construction operations. However, previous studies have shown that there is a lack of clarity on the environmental trade-offs between onsite and offsite construction. Factors that can affect the decision to build onsite or offsite include the availability of a local offsite manufacturing facility, the distance of the offsite factory to the final place of use, the proximity of the site to the local supply of material and labor, etc. This study provides a framework to apply the system dynamic modeling technique to evaluate how various factors can affect the environmental impact of the building construction phase (for onsite or offsite construction methods). The system dynamic model (using Vensim software) that was developed provides a platform that allows users to input variables such as the distance that is expected for transportation of labor, material, and equipment to both the onsite facility and the offsite construction location, factors associated with the use of equipment for construction, the distance needed for transportation of building panels or modules from the offsite facility to the final site, etc. Among other things, the model showed that an increase in the distance from the offsite yard to the final construction site increases the total impacts of transportation of completed modules. An increase in the number of trips for the transportation of material to the onsite construction location increases the total impact of onsite construction. In terms of the environmental impact of construction, none of the two methods of construction gives an absolute superiority over the other. The environmental performance of offsite and onsite depends on various associated factors. It is recommended that building practitioners review various factors that are peculiar to their projects to make an informed decision on the best construction methods.

Avian influenza (bird flu) occurs sporadically in American poultry flocks, decimating these flocks and causing substantial economic losses. Avian influenza also impacts the beliefs of food handlers and preparers in the home (home cooks). Although those who properly handle and prepare processed poultry products cannot succumb to avian influenza, there is a widespread belief that one can contract the bird flu from these foods. Beliefs about getting avian influenza from poultry products and intentions to avoid consuming poultry products are the focus of this study of 285 home cooks. False beliefs about getting avian influenza from handling, preparing, and consuming poultry products are apparent in this sample. Correlational analysis also shows that those holding the false beliefs intend to act upon those beliefs by planning not to consume poultry products. Moreover, the false beliefs about contracting avian influenza from poultry products are correlated with a bias to see oneself as less likely to produce food that contains foodborne diseases. These findings are consistent with, and contribute to, the research literatures on belief formation and change, behavioral intentions, and with research showing how guilt by association thought processes underlie false beliefs related to food safety. This research has important implications for poultry and other food processing industries, and for campaigns to persuade the public about real and imaginary risks associated with particular food products.

The aim of this article is to examine the impacts of Coronavirus Disease -19 (Covid-19) vaccines on economic condition and sustainable development goals. In other words, we are going to study the economic condition during Covid19. We have studied the economic costs of pandemic, benefits in terms of gross domestic product (GDP), public finances and employment, investment on vaccines around the world, progress and totally the economic impacts of vaccines and the impacts of emerging markets (EM) on achieving sustainable development goals (SDGs), including no poverty, good health and well-being, zero hunger, reduced inequality etc. The importance of emerging economies in reducing the harmful effects of the Corona has also been noted. We have tried to do experimental results and forecast daily new death cases from Feb-2020 to Aug-2021 in Iran using Artificial Neural Network (ANN) and Beetle Antennae Search (BAS) algorithm as a case study with econometric models and regression analysis. The findings show that Covid19 has had devastating economic and health effects on the world, and the vaccine can be very helpful in eliminating these effects specially in long-term. We observed that there is inequality in the distribution of Corona vaccines in rich countries compared to poor which EM can decrease the gap between them. The results show that both models (i.e., Artificial intelligence (AI) and econometric models) almost have the same results but AI optimization models can robust the model and prediction. The main contribution of this article is that we have surveyed the impacts of vaccination from socio-economic viewpoint not just report some facts and truth. We have surveyed the impacts of vaccines on sustainable development goals and the role of EM in achieving SDGs. In addition to using the theoretical framework, we have also used quantitative and empirical results that have rarely been seen in other articles.

Life cycle assessment, LCA is one of the tools that is used to measure the environmental impacts of a process or an operation. Various studies have mentioned the benefits of mass timber in building construction. This study presents an evaluation of the LCA of certain mass timber in relation to concrete-based materials. Using Athena impact estimator for buildings, the study compared the results of an LCA study for a house that is designed with concrete beams, concrete columns, and concrete walls with brick in the envelope category (Material group 1) with those that are made with glulam beams, glulam columns, CLT walls with spruce wood bevel siding (Material group 2), and another building with LVL columns, LVL beams, CLT walls with spruce wood bevel siding (Material group 3). The results are in line with those that were reported by the majority of previous researchers. For the location that is being reviewed (Calgary, Alberta), the designs showed that construction with wood materials having mass timber components will have a better environmental performance than that for a building design with more concrete-based materials. The building design with more concrete-based material (group 1) showed 242% and 60% higher global warming and acidification potential respectively than the building with glulam beams and columns (material group 2). Except for ozone depletion potential, material group 2 (with glulam beams and columns) has a lower impact than material group 3 (with LVL/PSL beams and columns). The differences in impacts are more pronounced when the comparison is with design with more concrete-based products. This report further shows that LCA can be helpful during the preliminary design to evaluate the expected environmental impacts of the choice of different materials. This study recommends that material manufacturers and building contractors pay attention to LCA results to evaluate areas for continuous improvement.