This article explores the integration of Artificial Intelligence (AI) in English as a Sec-ond Language (ESL) education, focusing on innovative teaching methods and authen-tic materials. AI-powered gamification is discussed, highlighting the use of AI tools like ChatGPT to enhance the gamification of key terms and concepts in ESL educa-tion. The interactive and enjoyable nature of gamified learning, combined with AI-driven content curation, deepens student understanding, critical thinking skills, and retention. By personalizing the learning experience, AI tools cater to individual stu-dent needs, allowing for flexibility in difficulty and fostering a love for the subject. Reflection and self-assessment play a crucial role in solidifying knowledge and pro-moting deeper learning. The article also discusses the importance of authentic materials in ESL education, emphasizing the use of AI-driven content curation to select and organize relevant and meaningful language content. AI-powered tools can analyze vast amounts of data, un-derstand patterns, and make accurate predictions, enhancing the user experience and delivering content that is most relevant and valuable to each individual student. The integration of AI in ESL education offers numerous benefits, including increased engagement, improved retention and application of key terms and concepts, personal-ized learning experiences, and enhanced critical thinking skills. By embracing AI-powered gamification and content curation, educators can create dynamic, interactive, and engaging learning experiences that foster a love for language learning and pro-mote deeper understanding.

Location determination algorithms are widely used in cellular networks, especially in the long-term evolution (LTE) network, to enable the provision of location-based services (LBS). The increasing global demand for cellular networks has resulted in the creation of new user equipment (UE) positioning systems that align with the network's momentum. Regrettably, all of these technologies are hindered by their incapacity to ascertain the location of the UE in distant regions. This article introduces a novel method utilizing Radio Frequency (RF) fingerprinting to precisely locate UEs in remote areas. The approach entails employing a proposed partitioning model with a high level of precision, incorporating artificial intelligence and machine learning AI/ML in its fundamental state to reduce the search area. Furthermore, two algorithms are suggested: The first aims to enhance the efficiency of the battery with limited capacity by decreasing the frequency of measurements transmission. The second utilizes Jaccard similarity and incorporates the prefix filtering technique to determine matches. The algorithm is used to speed up the process of matching the fingerprint recorded in the fingerprint database with the fingerprint captured in real time. The results shows that it can reduces the transmission rate by 77.08% and achieves the lowest error rate of 35.34 m. Additionally, it exhibits a response time of 8 seconds.

The excessive exploitation of natural resources brings with it a growing environmental problem, which is largely due to industrial development. Different international treaties, conventions, and protocols try to mitigate the impacts of global warming. However, new tools are constantly needed to achieve the sustainability of economies and the preservation of renewable resources. In response to this, green bonds arise providing a coherent solution that integrates both the industry and the environment. These bonds constitute a financial instrument allowing the collection of resources, with the only requirement of being invested in sustainable projects generating environmental and social well-being. This paper highlights Colombia's potential as an emerging market attractive for investments classified as green. This Colombian green market is expected to grow, due to the low amounts of GHG emissions compared to the industrialized countries and the richness in natural resources of the nation. However, to develop sustainable energy projects in Colombia, special instruments are required to enhance the promotion and financing of energy projects. For this reason, various financing alternatives to the traditional systems for the development of clean energy must be evaluated. This paper emphasizes the potential of green bonds to improve energy projects in Colombia and obtain additional benefits to reduce climate change through the use of sustainable renewable energies. Through a document review exercise in specialized literature and the application of a case study, the advantage of green bonds over other traditional mechanisms for financing initiatives for small and medium enterprises is demonstrated.

The study examined the effect of the choice of successor on post succession business survival of small and medium-scale family enterprises. The study employed survey research design with the use of primary data obtained from small and medium-scale family enterprises in Osun State, Nigeria, through the instrument of questionnaire. A sample of 150 small and medium-scale enterprises drawn from five LGAs using both purposive and random sampling approach was adopted. The study adopted inferential analytic methods of factor analysis and general linear regression. The t-test statistic, at 0.05 level of significance showed t-value of 11.026, at p =0.000. The study therefore concluded that there is significant relationship between entrepreneurial succession decision (choice of successor) and business survival of small and medium-scale family enterprises, and recommended that succession decision should aim at individuals who possess the characteristics that enable business survival.

The research focused on determining the influence of ICT tools in improving reading comprehension in second grade secondary school students. A quantitative approach and a quasi-experimental design were used, with a sample of 74 students divided into two groups: one experimental and one control. A questionnaire validated by experts was applied for data collection and the Jasp program was used for data analysis, using the Mann-Whitney U coefficient. The results showed that reading comprehension improves significantly (p<.05) with a large effect size after the application of ICT tools. It is concluded that reading comprehension is a skill that can be improved through the application of educational programs that incorporate digital tools. These findings suggest the importance of implementing digital technologies in the educational field to improve students' reading comprehension.

A sequence-to-sequence model is used as the foundation for a suggested abstractive Arabic text summarizing system. Our goal is to create a sequence-to-sequence model by utilizing multiple deep artificial neural networks and determining which one performs the best. The encoder and decoder have been developed using several layers of recurrent neural networks, gated recurrent units, recursive neural networks, convolutional neural networks, long short-term memory, and bidirectional long short-term memory. We are re-implementing the fundamental summarization model in this study, which uses the sequence-to-sequence framework. Using a Google Colab Jupiter notebook that runs smoothly, we have constructed these models using the Keras library. The results further demonstrate that one of the key techniques that has led to breakthrough performance with deep neural networks is the use of Gensim for word embeddings over other text representations by abstractive summarization models, along with FastText, a library for efficient learning of word representations and sentence classification.

Introduction: Excessive consumption of sugary drinks increases the risk of obesity and negatively affects nutritional health because they contain additional sugars and empty calories. Making well-informed decisions that prioritize nutrient-dense options enables people to reduce health risks and improve their general nutritional state. Objectives: The objectives of this study to is to assess the relationship between nutritional status, dietary knowledge and sugary beverage consumption habits among secondary school children in Lahore. Methodology: A cross-sectional study was conducted among a sample of 384 secondary school children studying in public and private schools of Lahore, Pakistan and data was collected through a combination of 2 validated questionnaires, composed of 4 parts (personal information, frequency of sugary beverages consumed, sugary beverage consumption pattern and & dietary knowledge). For BMI calculation, height and weight were measured. Data analysis was done through SPSS version 23. Results: The study reveals that 51.8% of the students in Pakistani secondary schools in Lahore fell within the normal BMI limit. The remainder, however, were malnourished; 13% of the adolescents were underweight, 21.6% were overweight, and 13.5% were obese. Furthermore, it was found that there was no significant relationship between dietary knowledge, use of sugary beverages, and nutritional status. Conclusion: In conclusion, it is evident that the consumption of sugary sweet beverages among the secondary school children of Lahore, Pakistan is significantly higher. Also, the burden of malnutrition and the body mass index is significantly high among these adolescents, associated with SSB consumption. However, BMI is no significantly related to dietary knowledge.

The purpose of this study was to investigate the impact of the interactive model known as "Exelearning.net" on improving reading comprehension skills among students of Basic Superior in Santa Elena, Ecuador. An experimental study with a quantitative approach was conducted, involving a sample of 70 students divided into two groups of 35. Pre and post-tests were administered to assess reading comprehension. Statistical analyses revealed significant improvements in the dimensions of literal, inferential, and critical comprehension, with higher scores in the experimental group than in the control group. The results showed a significance level of < 0.001, indicating that the application of the interactive model ExeLearning.net had a positive impact on strengthening students' reading comprehension skills. These findings suggest that using interactive programs can facilitate the relationship between reading and text comprehension.

Many practitioners and investors have praised the use of licensing to enhance competition in the telecom sector due to its real effects on the Nigerian economy. However, since 2011, subscribers in the industry have had a mixed experience with the license issue due to problems with telecom companies' exploitative tendencies and antics, which make it difficult for customers to acquire reliable and reasonably priced telecoms services. With a focus on the institutional and legal safeguards put in place by the government to ensure that the operators abide by the licensing and regulation powers granted to them by the law, the study essentially examines how licensing affects competition among telecom operators and the expansion of mobile telecom networks in Nigeria. The paper's methodology adopted the documentary approach, and the data were ostensibly gathered from secondary sources and examined in terms of substance. Neo-liberal theory of the state provided a sufficient theoretical foundation for the examination of the study. The paper's findings demonstrate that while the expansion of Nigeria's mobile telecom networks is aided by the use of licensing to promote competition among telecom operators, consumers' access to affordable and high-quality telecommunications services is restricted by the exploitative tendencies and antics of telecom companies. The paper's suggestions were based on these findings, and one of them was that Telecommunications service tariffs must always be cost-oriented and reflect the actual costs borne by operators to provide the services in question.

Metal nanoparticles and activated carbon-based nanocomposite materials are gaining popularity due to their numerous potential applications in a wide range of materials science areas. The current study aims to create novel photocatalyst frameworks for nanocomposites that were synthesized from biogenic waste and used to photodegrade methylene blue (MB) in wastewater under visible light. The activated carbon from date seeds was calcinated at a temperature of 700°C for two hours, and its surface was improved using zinc oxide nanoparticles and calcium oxide nanoparticles manufactured from eggshells at 900oC. XRD, FT-IR, SEM, BET, and TEM analyses were used to characterize the produced nanocomposites. The synthesized nanocomposite photocatalytic activity was evaluated by degrading MB dyes, its model of water pollution. The results showed that the nanocomposite CaO/AC/ZnO has a mesoporous structure with great sorption capability. Also, the photodegradation efficiency of MB using AC, CaO, AC/ZnO, and CaO/AC/ZnO nanocomposite was 33.23, 37.58, 54.61, and 88.92%, respectively, after100 min of sunlight irradiation indicating that photodegradation efficiency increases by improving the surface properties of AC. The CaO/AC/ZnO nanocomposite exhibited a 96.7% removal efficiency of MB following 120 min of visible light radiation exposure. Therefore, the CaO/AC/ZnO nanocomposite has a promising opportunity to function as a versatile and effective photocatalyst for photodegradation of organic dyes in wastewater.