This inquiry endeavors to meticulously examine the intricate dynamics of the symbiotic developmental interplay among the gaming, tourism, and economic sectors in Macau. Utilizing the methodology of deviation standardization, the data undergoes scrupulous processing, invoking the entropy method to ascertain the weights of diverse evaluative indices. The developmental trajectories of Macau’s gaming, tourism, and economic domains spanning the years 2011 to 2021 are fastidiously gauged. Subsequently, a sophisticated coupled coordination model is employed to delve into the nuanced systemic interdependencies characterizing their developmental relationships. From 2011 to 2021, the holistic progression of Macao’s gaming and tourism sectors has exhibited a discernible ascent over the temporal continuum. Concurrently, the degree of coupling coordination has advanced from a state of near coordination to a commendable level of synchronized development. The overarching system of Macau’s gaming and tourism industries has transitioned from a state of disarray to one of ordered harmony, with the correlative impact of Macau’s tourism sector being adeptly realized. The supporting role played by Macau’s gaming industry in fortifying the tourism sector is conspicuously manifest. The alignment and coordination between Macau’s gaming and tourism sectors exhibit fluctuations across distinct developmental stages. During phases of nascent development in both the gaming and tourism domains, a palpable imbalance prevails. Elements such as the proliferation of gaming enterprises, international tourism revenue, aggregate output value of gaming establishments, market share held by gaming enterprises, and the profit margins thereof have, to a certain extent, impinged upon the harmonized evolution of the tripartite subsystems. This study proffers recommendations to foster the optimization and elevation of the industrial structure while championing the integration and advancement of diverse sectors. It advocates for the amplification of the propulsive impetus intrinsic to the gaming industry, coupled with the enrichment of the tourism product portfolio. Furthermore, it espouses the establishment of an effective mechanism for high-quality development, tailored to the exigencies of the contemporary era. This involves the implementation of precise policies, the facilitation of amalgamated progress in gaming and tourism, and an unwavering commitment to sustainable development through the interconnected alignment of gaming, tourism, and the broader economy. The findings of this study furnish a scientific foundation for the strategic industrial planning and developmental initiatives undertaken by relevant departments in Macau.

In this study, we utilized a convolutional neural network (CNN) trained on microscopic images encompassing the SARS-CoV-2 virus, the protozoan parasite “plasmodium falciparum” (causing of malaria in humans), the bacterium “vibrio cholerae” (which produces the cholera disease) and non-infected samples (healthy persons) to effectively classify and predict epidemics. The findings showed promising results in both classification and prediction tasks. We quantitatively compared the obtained results by using CNN with those attained employing the support vector machine. Notably, the accuracy in prediction reached 97.5% when using convolutional neural network algorithms.

Objective/Aim: In the context of a constantly changing legislative environment and the necessity for professionals to develop their skills, the research focuses on identifying effective methods and tools that facilitate efficient learning and professional development in the field of labour law. This study aimed to propose a pedagogical technology for the preparation and training of specialists in the field of labour law and to assess the effectiveness of the training based on the specified technology. Method: The study involved 124 participants, with 63 in the experimental group and 61 in the control group. Statistical analysis was performed using Microsoft Excel. The student’s t-test indicated significant improvements in the experimental group’s training effectiveness, confirming the proposed pedagogical technology’s efficacy. Results: Consequently, implementing training and education technology for specialists in the labour law field was proposed to enhance the indicators. The criteria for the preparation of specialists in the field of labour law were delineated, including knowledge of labour legislation, consulting and support skills, analytical skills, communication skills, and continuous learning. According to the criteria above, levels of preparation for specialists in the field of labour law were established, namely high, medium, and essential. The proposed training and education technology for specialists in the field of labour encompasses the following tools: The utilisation of online platforms and educational resources, virtual classes and simulations, the incorporation of multimedia materials, the integration of adaptive learning technologies, the implementation of project- and problem-oriented teaching methodologies, the incorporation of interactive methodologies, the incorporation of cloud technologies and mobile applications, and the provision of assessment and feedback. Conclusion: The proposed pedagogical technology effectively enhances the training and education of labour law specialists. The experimental group’s significant improvement in learning outcomes confirms the technology’s efficacy. Implication: The findings of this research hold significant social implications. Improved training and education of labour law specialists leads to a more competent and effective legal workforce. This, in turn, ensures better protection of workers’ rights and fairer employer-employee relations, contributing to overall social stability.