This study explores the determinants of control loss in eating behaviors, employing decision tree regression analysis on a sample of 558 participants. Guided by Self-Determination Theory, the findings highlight amotivation (β = 0.48, p < 0.001) and external regulation (β = 0.36, p < 0.01) as primary predictors of control loss, with introjected regulation also playing a significant role (β = 0.24, p < 0.05). Consistent with Self-Determination Theory, the results emphasize the critical role of autonomous motivation and its deficits in shaping self-regulation. Physical characteristics, such as age and weight, exhibited limited predictive power (β = 0.12, p = 0.08). The decision tree model demonstrated reliability in explaining eating behavior patterns, achieving an R² value of 0.39, with a standard deviation of 0.11. These results underline the importance of addressing motivational deficits in designing interventions aimed at improving self-regulation and promoting healthier eating behaviors.

Researchers at Stanford University in the USA identified the world's Top 2% of Scientists based on data from the Scopus database. This study recognized leading scientists across various sub-fields, ranking them by the sm-subfield-1 (ns) indicator. A total of 174 distinguished scientists from 25 countries were highlighted, with a notable concentration from the USA. Harvard University was a leader, producing top scientists in 16 sub-fields. Among the 174 recognized, four are Nobel Prize Laureates, and two have received the Fields Medal. Ten scientists authored the most frequently cited papers across categories in the Web of Science, including the Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), and Arts & Humanities Citation Index (A&HCI). Professor Georg Kresse authored the most cited paper in three Web of Science categories: multidisciplinary materials science, applied physics, and condensed matter physics. The study further analyzed GDP and population metrics for each top scientist by sub-field. Seventy of the 174 scientists have consistently maintained their top rankings over the past five years.

The centers of trade and economic activities in the region of Southeast Asia rank from a huge and modern to a small and traditional pattern. Malacca and Singapore have been cases in point for huge and modern patterns, while the border areas in eastern Indonesia, East Malaysia, and the Philippines are the cases for small and traditional centers. This paper will argue that with global connectivity and regional dynamics, the small and traditional trade and economic centers could shift to modern ones. History records that the introduction of the Southeast Asian region by the outside world, especially in relation to trade and economic activities, was largely derived from the significant role played by the people in the mainland of Southeast Asia regarding the silk roads route and the role of the people in the insular or islands of Southeast Asia regarding the spice trade route in the premodern time. Later in the modern time in Southeast Asia, the role of Islam, the Europeans and the center trade of Malacca around the 17th and 18th centuries played a significant role. Indeed, huge trade centers like Malacca in the 17th C and 18th C and later by Singapore in the 9th C have been very important throughout the history of trade in the Southeast Asian region. However, we must not ignore the roles of the border areas in the Southeast Asian archipelago, especially in eastern Indonesia, East Malaysia, and the border region of the Philippines which have played a dominant role in trade and economic activities. These activities have been smaller and more traditional than the Malacca and Singapore cases, but economic activities could develop rapidly with the global connection and its interconnectivity. Besides, those border areas have also become an important key for security issues not only in the Southeast Asia region in particular but also in the Asia Pacific or Indo Pacific region as well. The security of the region of Southeast Asia and even Indo Pacific could be affected by the situation in those border areas. Interconnectivity is a challenge as well as an opportunity for these border areas to become the future of trade and economic activities within the region of Southeast Asia that also connects with the region of Indo Pacific, especially China, South Korea, and Taiwan. The planning of Indonesian capital movement to East Kalimantan will add opportunities for those border areas located near the proposed new capital. About the above issues, this paper will address several issues: firstly, the history of trade and economic activities in Malacca, Singapore, and the border areas in eastern Indonesia, East Malaysia, and the Philippines; secondly, the different patterns of trade and economic developments of the Malacca, Singapore, and the border areas in eastern Indonesia, East Malaysia, and Philippines; thirdly, the challenges and opportunities of the border areas in eastern Indonesia, East Malaysia, and the Philippines to develop bigger trade centers in the future; fourth, the interconnectivity of those border areas to Asia Pacific region. This paper uses an interdisciplinary approach in the fields of social sciences and humanities. With this study, it is hoped that a better understanding of regional dynamics will be obtained, especially in the border areas. The period that we use is from 1998 until present time regarding if there was changing policy due to the end of Old Order to the Reformation period of Indonesian government. As a result, the development of border areas had been in existence before the colonial time in which people moved freely and had trade contacts. Even though they used to have the same ethnic linkage, after the formation of a modern state where they have different citizenships, in reality they can relate to each other in harmony and peace because of the similarity of ethnic linkages they had in the past. Colonial powers intended to replace the powers of traditional kingdoms with the idea of civilizing the colonializ

Accurate drug-drug interaction (DDI) prediction is essential to prevent adverse effects, especially with the increased use of multiple medications during the COVID-19 pandemic. Traditional machine learning methods often miss the complex relationships necessary for effective DDI prediction. This study introduces a deep learning-based classification framework to assess adverse effects from interactions between Fluvoxamine and Curcumin. Our model integrates a wide range of drug-related data (e.g., molecular structures, targets, side effects) and synthesizes them into high-level features through a specialized deep neural network (DNN). This approach significantly outperforms traditional classifiers in accuracy, precision, recall, and F1-score. Additionally, our framework enables real-time DDI monitoring, which is particularly valuable in COVID-19 patient care. The model’s success in accurately predicting adverse effects demonstrates the potential of deep learning to enhance drug safety and support personalized medicine, paving the way for safer, data-driven treatment strategies.

The purpose of Vehicular Ad Hoc Network (VANET) is to provide users with better information services through effective communication. For this purpose, IEEE 802.11p proposes a protocol standard based on enhanced distributed channel access (EDCA) contention. In this standard, the backoff algorithm randomly adopts a lower bound of the contention window (CW) that is always fixed at zero. The problem that arises is that in severe network congestion, the backoff process will choose a smaller value to start backoff, thereby increasing conflicts and congestion. The objective of this paper is to solve this unbalanced backoff interval problem in saturation vehicles and this paper proposes a method that is a deep neural network Q-learning-based channel access algorithm (DQL-CSCA), which adjusts backoff with a deep neural network Q-learning algorithm according to vehicle density. Network simulation is conducted using NS3, the proposed algorithm is compared with the CSCA algorithm. The find is that DQL-CSCA can better reduce EDCA collisions.

The study documents the model of the knowledge transfer process between the University, the Vocational Training Center and the industrial actors. The research seeks to answer to the following questions. Where is new knowledge generated? Where does knowledge originate from? Is there a central actor? If so, which organization? Hypotheses tested by the research: H1: Knowledge starts from the higher education institution. H2: Most “new knowledge” is generated in universities and large multinational companies. H3: The university is a central actor in the knowledge flow, transmitting both hard and soft skills, as well as subject (‘know-what’), organizational (‘know-why’), use (‘know-how’), relational (‘know-who’), and creative (‘care-why’) knowledge. The aim of the research is to model the way of knowledge flow between the collaborating institutions. The novelty of this research is that it extends the analysis of the knowledge flow process not only to the actors of previous researches (higher education institutions, business organizations, and government) but also to secondary vocational education and training institutions. The methodology used in the research is the analysis of the documents of the actors investigated and the questionnaire survey among the participants. Knowledge transfer is the responsibility of the university and its partner training and business organizations. In vocational education and training, knowledge flows based on the knowledge economy, innovation and technological development are planned, managed and operational. The research has shown that knowledge is a specific good that it is indivisible in its production and consumption, that it is easy and cheap to transfer and learn.

The objective of this research paper is to investigate potential avenues for value creation in the refined sugar market for domestic use, a market currently facing a critical juncture. The growing concerns about the health impacts of sugar have resulted in a notable decline in demand. Furthermore, changes in European Union regulations have introduced additional operators into the Spanish market, increasing competition and amplifying the need for innovation. This study examines how brands can respond to these challenges by enhancing their value proposition through market segmentation, targeted marketing strategies, and adaptive packaging solutions. To achieve this objective, we have conducted market research, which involved an in-depth interview, and a questionnaire distributed to 402 individuals responsible for household purchases. The findings suggest potential approaches for addressing the needs of consumers with a focus on health and well-being, while simultaneously enhancing the durability of products, thus facilitating greater brand differentiation. Furthermore, the study underscores the pivotal role of public policies and regulatory frameworks in influencing consumer behavior and market dynamics. Policies promoting sugar alternatives, labelling requirements, and packaging innovations have been demonstrated to impact brand strategies and consumer preferences. By aligning with these policy-driven shifts, companies can enhance their positioning in a mature and competitive market. This research contributes to the existing literature on brand value in commodity markets by integrating insights into the impact of regulation and consumer segmentation. Our recommendations emphasize the importance of marketing strategies that are informed by an understanding of the policy context, which not only enhances brand equity but also promotes sustainable growth in the retail sugar industry.

This research uses both quantitative and qualitative research methodologies to examine the complex factors affecting community resilience in various settings. In this case, the research explores how social cohesion, governance effectiveness, adaptability, community involvement, and the specified difficulties influence resilience results by using the five pillars of resilience as variables. Descriptive and inferential statistics are used to test hypotheses on the relationships between social cohesion, governance effectiveness, adaptive capacity, and community resilience variables. Qualitative data provides further insights into the quantitative results by providing broader views and experiences of the community. The study shows how social capital is important in increasing community capacity, stressing the importance of social relations and trust in developing community solutions to disasters. Another major factor that stands out is the governance factor that ensures that decisions are made, and actions taken in line with the community’s best interest in improving its ability to prepare for and respond to disasters. Adaptive capacity is seen as a key component of resilience and this paper emphasizes the importance of communities to come up with measures that can be adjusted to the changing circumstances. In summary, this study enriches theoretical understanding and offers practical applications of the processes that can enhance community resilience based on the principles of social inclusion, sound governance, and context-specific solutions.