Technological management has promoted distinctive characteristics in the socio-productive development of the regions. Its usefulness in entrepreneurial activity is studied to design the architecture of a technological observatory as an intelligent system for entrepreneurship in Latin America. Using a descriptive-explanatory method, data obtained from the application of two instruments directed to 18 experts in information and communication technologies and 174 entrepreneurs distributed 92 in Lima-Peru and 82 in Santiago de Cali-Colombia are processed. The findings show informational and training barriers and a weak or non-existent technological platform for effective entrepreneurial development. Added to the low development of plans and alliances mediated by technologies, whose experience supports public policies that strengthen entrepreneurship as an emerging economy. The architecture supports the functional and operational aspects of the system. Its scalability in other regions dynamizes the services-processes required prior to the detection of needs directed towards the projection of sustainable entrepreneurship.

This paper presents a numerical method for solving a nonlinear age-structured population model based on a set of piecewise constant orthogonal functions. The block-pulse functions (BPFs) method is applied to determine the numerical solution of a non-classic type of partial differential equation with an integral boundary condition. BPFs duo to the simple structure can efficiently approximate the solution of systems with local or non-local boundary conditions. Numerical results reveal the accuracy of the proposed method even for the long term simulations.

Tomato (Solanum lycopersicon L.) is a highly valued crop in the world, particularly in Nigeria with high nutritional and economic benefits. However, its production in Iwollo, Southeast Nigeria, is constrained by unfavorable weather conditions. To address this, a study was conducted at the Teaching and Research Farm, Department of Horticultural Technology, Enugu State Polytechnic, Iwollo, Southeast Nigeria to evaluate and select the best cultivar for high tunnel production using the Rank Summation Index. Completely Randomized Design with three replications was used, and six high-yielding cultivars, namely Roma VF, BHN-1021, Supremo, Pomodro, Money maker, and Iwollo local, were evaluated. Data were collected on key agronomic characters and analyzed with Analysis of Variance (ANOVA) at a 0.05 level of probability. There were significant differences in the number of leaves per plant, plant height, number of branches per plant, days to fruit maturity, fresh fruit weight, number of harvested fresh fruits per plant, and fresh fruit yield per plant among the cultivars. These characters that showed significant differences were ranked and summed up to obtain the Rank Summation Index (RSI) score. The results revealed that the Supremo cultivar had the lowest and best score (18). This suggests Supremo as the best cultivar for high tunnel tomato production in the study area, based on its superior performance across key agronomic traits.

This study introduces a cross-country comparative analysis of the role of News Ombudsperson in the public media corporations in Spain and France. It investigates the specific media self-regulatory processes established to reduce reputational risks and increase the trust and credibility of the media organisations. It aims to fill in the gaps in prior research by applying a qualitative framework developed using indicators derived from scholarly work on regulation and governance and media management. The variables selected for the analysis are extracted from prior interdisciplinary research and focus on media self-regulatory processes, complaints management mechanisms, election, reporting procedures, checks and balances, roles, visibility and transparency of News Ombudspersons in two countries which represent the Polarised Pluralist media system category. Research questions are raised in relation to the main variables identified for the comparative analysis. Data were collected from multiple publicly available international sources, including public media organizations databases, national media regulatory authorities, and academic studies. Results reveal cross-country variations. The systematic investigation of different forms of self-regulatory procedures might lead to concrete recommendations and best practice models for media organizations beyond the European Union. Further research could address the role of media audiences as relevant stakeholders in media governance processes.

The incorporation of artificial intelligence (AI) into language education has created new opportunities for improving the instruction and acquisition of Chinese characters. Nevertheless, the cognitive difficulties linked to the acquisition of Chinese characters, such as their intricate visual features and lack of clear meaning, necessitate thoughtful deliberation when developing AI-supported learning interventions. The objective of this project is to explore the capacity of a collaborative method between humans and machines in teaching Chinese characters, utilising the advantages of both human expertise and AI technology. We specifically investigate the utilisation of ChatGPT, a substantial language model, for the creation of instructional materials and evaluation methods aimed at teaching Chinese characters to individuals who are not native speakers. The study utilises a mixed-methods approach, which involves both qualitative examination of lesson plans created by ChatGPT and quantitative evaluation of student learning outcomes. The results indicate that the suggested framework for human-machine collaboration can successfully tackle the cognitive difficulties associated with learning Chinese characters, resulting in enhanced learner involvement and performance. Nevertheless, the research also emphasises the constraints of AI-generated material and the significance of human involvement in guaranteeing the accuracy and dependability of educational interventions. This research adds to the expanding collection of literature on AI-assisted language learning and offers practical insights for educators and instructional designers who aim to use AI tools into Chinese language curriculum. The results emphasise the necessity of employing a multi-disciplinary strategy in AI-supported language learning, incorporating knowledge from cognitive psychology, educational technology, and second language acquisition.

Disinformation can be defined as false information deliberately initiated to cause harm to a person, social group, organization, or country. Gendered disinformation then attacks or undermines people based on gender or weaponizes gendered narratives for political, social, or economic objectives. Gendered disinformation comes in different forms, such as harmful social media posts and graphics, sexual fabrications, and other forms of conspiracy theories. It is used in various situations and at different places. This research discussed the instances of gendered disinformation and harmful online narratives that are recognizable and visible. It sheds light on the potential direct and indirect impact on youth experiences. In this study, the young participants (aged 18–30) focused on the instances of the existing online narratives of gendered discrimination from Belgium, Greece, Latvia, Spain, and Türkiye. The research provided an initial analysis of what “gendered information and harmful online narratives” look like and some recommendations from youth perspectives on countering the issues. The study concluded that there is a need for more research, further harmonization of legal frameworks, and strengthened capacity to detect gendered disinformation, propaganda, and hate speech.