The R3A Route represents a collaborative initiative involving the governments of Thailand, Laos, and China aimed at bolstering connectivity along the North-South Economic Corridor, as a vital component of the Greater Mekong Subregion Economic Cooperation Program (GMS). Since its inception in 2008, this endeavor has substantially enhanced the logistical framework between Thailand, Laos, and China. However, it has also revealed an imbalance in the benefit distribution of value chains within the tourism industry. One of the fact that, local stakeholders in each country often leverage their home country’s advantages, leading to the exploitation of counterparts with lower capacity in other nations. This unfair utilization goes against the initial intentions of fostering collaboration among these countries. Given China and its development as a starting point for tourism and its popularity among tourists traveling this route, this study provides a comprehensive analysis of China’s policy and insights of its influences on R3A tourism development in Laos and Thailand. The study constructs a content analysis with an umbrella of stakeholder analysis based on reliable data and is cross-verified through data triangulation. The findings lead to recommendations aimed at making Thai-Lao-Chinese tourism cooperation more sustainable and effective.

Breast cancer was a prevalent form of cancer worldwide. Thermography, a method for diagnosing breast cancer, involves recording the thermal patterns of the breast. This article explores the use of a convolutional neural network (CNN) algorithm to extract features from a dataset of thermographic images. Initially, the CNN network was used to extract a feature vector from the images. Subsequently, machine learning techniques can be used for image classification. This study utilizes four classification methods, namely Fully connected neural network (FCnet), support vector machine (SVM), classification linear model (CLINEAR), and KNN, to classify breast cancer from thermographic images. The accuracy rates achieved by the FCnet, SVM, CLINEAR, and k-nearest neighbors (KNN) algorithms were 94.2%, 95.0%, 95.0%, and 94.1%, respectively. Furthermore, the reliability parameters for these classifiers were computed as 92.1%, 97.5%, 96.5%, and 91.2%, while their respective sensitivities were calculated as 95.5%, 94.1%, 90.4%, and 93.2%. These findings can assist experts in developing an expert system for breast cancer diagnosis.

Personality traits refer to enduring patterns of emotions, behaviors, and thoughts that shape an individual’s distinct character, influencing how they perceive and engage with their environment. This quantitative study aims to underscore the influence of personal factors and the role of educational institutions in mapping sustainable green entrepreneurial intentions among university students in Saudia Arabia. To examine the impact of personality traits and entrepreneurship education on students’ green initiatives, the research employs a quantitative research method, collecting data through a structured questionnaire survey from 494 participants who enrolled in the entrepreneurship education at King Faisal University. Structural equation modeling via SmartPLS 3 is employed for data analysis. The study reveals significant associations between the need for achievement, proactiveness, risk-aversion, self-efficacy, and entrepreneurship education with green entrepreneurial intentions. Our research findings demonstrate that the inclusion of entrepreneurship education in the curriculum has a noteworthy and favorable influence on the intention to engage in green entrepreneurship (β = −0.105, t = 3.270, p < 0.001). Additionally, it is worth noting that the desire for achievement remains significantly associated with the intention to engage in green entrepreneurship (β = 0.120, t = 3.588, p < 0.000). Furthermore, the proactive behavior of individuals has a positive and constructive impact on the intention to engage in green entrepreneurship (β = 0.207, t = 4.272, p < 0.000). Similarly, the inclination to avoid risk is found to have a beneficial and significant influence on the intention to engage in green entrepreneurship (β = 0.336, t = 4.594, p < 0.000). Lastly, it is worth highlighting that individuals’ belief in their own abilities, referred to as self-efficacy, is positively and significantly linked to the intention to engage in green entrepreneurship (β = 0.182, t = 2.610, p < 0.009). The research carries social, economic, and academic implications by emphasizing the positive contribution of green entrepreneurs to the future. Practical recommendations for policymakers and decision-makers are provided.

Background: The background and objectives of the research revolve around bureaucracy as a classic form of the modern division of labor, with Max Weber acknowledging its inevitability. However, the objective implications of the bureaucracy’s iron cage are evident in governance and management experiences. The mayors of Tehran’s districts exemplify how Iranian culture interacts with bureaucracy. This research seeks to establish principles and governance for district governors using an alternative bureaucracy, parallel to conventional bureaucracy. Methods: The methods employed include twenty strategically selected interviews, considering age, municipal area, and work experience for maximum variance. Grounded theory methodology, specifically the approach by Anselm Strauss and Barney Glaser, guides the research, employing open coding, axial coding, and selective coding. MaxQDA 2020 software enhances the qualitative data analysis, facilitating organization, coding, and collaboration within the research team. Results: Findings indicate “inevitable violations” as a common starting point for interviewees, leading to three axes: “preconditions,” “objectives,” and “strategies and mechanisms” of alternative bureaucracy. In conclusion, breaking through bureaucracy becomes necessary for governors to act. Alternative bureaucracy, rooted in experience yet considering the bureaucratic field, requires transcendent goals. Hybridity and ethical principles are crucial when transitioning from conventional bureaucracy to the alternative in urban governance.

COVID-19 has presented considerable challenges to fiscal budget allocations in developing countries, significantly affecting decisions regarding number of investments in the transport sector where precise resource allocation is required. Elucidating the long-term relationship between public transport investment and economic growth might enable policymaker to effectively make a decision in regard to those budget allocation. Our paper then utilizes Thailand as a case study to analyze the effects on economic growth in a developing country context. The study employs Cointegration and Vector Error Correction Model (VECM) techniques to account for long-term correlations among explanatory variables during 1991–2019. The statistical findings reveal a significantly positive correlation between transport investment and economic growth by indicating an increase of 0.937 in economic growth for every one-percent increment in transport investment (S.D. = 0.024, p < 0.05). This emphasizes the potential of expanding the transport investment to recover Thailand’s economy. Furthermore, in terms of short-term adjustments, our results indicate that transport investment can significantly mitigate the negative impact of external shocks by 0.98 percent (p < 0.05). These findings assist policymakers in better managing national budget allocations in the post-Covid-19 period, allowing them to estimate the duration of crowding-out effects induced by shocks more effectively.

The provided material presents a priority article on the scientific discovery titled “The phenomenon of simultaneous destruction of water-oil and oil-water emulsions”. The authors propose the corresponding formula: the previously unknown phenomenon of simultaneous destruction of water-oil and oil-water emulsions occurs when polynanostructured surfactant demulsifiers with characteristics akin to crystalline liquids, intramolecular interblock activity, and enduring intramolecular nanomotors (such as block copolymers of ethylene and propylene oxides, which act as sources of oligomer homologues of oxyethylene ethers) are added to crude oil during primary oil processing. This phenomenon is attributed to the redistribution of oligomer homologues, with the most hydrophobic oxyethylene ethers being dispersed in water-oil emulsions and the most hydrophilic ones in oil-water emulsions, resulting in robust nanodispersed phases with crystalline liquid properties.