This study critically examines the implications of international transport corridor projects for Central Asian countries, focusing on the Western-backed Transport Corridor Europe-Caucasus-Asia (TRACECA), the Chinese initiative “One Belt—One Road”, and the International North-South Transport Corridor (INSTC) supported by the Russian Federation, India, and Iran. The analysis underscores the risks associated with Western projects, highlighting a need for a more explicit commitment to substantial infrastructure investments and persistent contradictions among key investors and beneficiaries. While the Chinese initiative presents significant benefits such as transit participation, infrastructure development, and economic investments, it also carries risks, notably an increased debt burden and potential monopolization by Chinese corporations. The study emphasizes that Central Asian countries, though indirect beneficiaries of INSTC, may not be directly involved due to geographical constraints. Study findings advocate for Central Asian nations to balance foreign investments, promote economic integration, and safeguard political and economic sovereignty. The study underscores the region’s wealth of natural and human resources, emphasizing the potential for increased demand for goods and services with improved living standards, strategically positioning these countries in the evolving global economic landscape.

The convergence of multifaceted global challenges encompassing the rise of populism, Brexit, the climate crisis, the COVID-19 pandemic, and the Russian invasion of Ukraine has catalyzed a profound reassessment of international trade policies. This article critically examines the intricate linkages between these challenges and their profound implications for the contemporary international trading system. Traditionally, globalization debates in the 1990s underscored the social and environmental dimensions of trade, yet the current landscape reveals an undeniable entwining of societal implications with trade policies. This article delves into the interconnectedness of these global challenges with trade, evaluating how each phenomenon influences and reshapes policy discourse. In particular, the rise of populism and its attendant protectionist sentiments have engendered a reevaluation of trade relationships and multilateral agreements. The seismic geopolitical event of Brexit has disrupted regional trade dynamics, signaling a paradigm shift in established trade blocs. Simultaneously, the imperatives of addressing the escalating climate crisis have spotlighted the necessity for trade policies to align with environmental sustainability goals. The COVID-19 pandemic, acting as a disruptor on a global scale, has accentuated vulnerabilities within supply chains, emphasizing the need for resilience and adaptability in trade frameworks. Additionally, the Russian invasion of Ukraine has introduced geopolitical tensions that further complicate the trade-policy landscape. By critically evaluating these intersecting challenges, this article delineates the evolving nature of trade policies and their inextricable relationship with societal and geopolitical realities. It underscores the imperative for a holistic approach in policy formulation that integrates social, environmental, and geopolitical considerations, acknowledging the integral role of trade policies in addressing contemporary global challenges.

Currently there is a great acceptance in medicine and dentistry that clinical practice should be “evidence-based” as much as possible. That is why multiple works have been published aimed at decreasing radiation doses in the different types of imaging modalities used in dentistry, since the greater effect of radiation, especially in children, forces us to take necessary measures to rationalize its use, especially with Cone Beam computed tomography (CBCT), the method that provides the highest doses in dentistry. This review was written using such an approach with the purpose of rationalizing the radiation dose in our patients. In order to formulate recommendations that contribute to the optimization of the use of ionizing radiation in dentistry, the SEDENTEXCT project team compiled and analyzed relevant publications in the literature, guidelines that have demonstrated their efficiency in the past, thus helping to see with different perspectives the dose received by patients, and with this, it is recommended taking into account this document so as to prescribe more adequately the complementary examinations that we use on a daily basis.

The research addresses the importance of ethics in public administration, focusing on public servants in the municipality of Rionegro, Colombia. Ethics is presented as an essential element to promote transparency and combat corruption in public management. Despite the fact that the 1991 Constitution establishes ethical principles, their application in practice remains a challenge, with a high level of immorality in public service. The study highlights the diversity of professional profiles in public servants, which hinders consistent ethical management. In addition, it mentions that many civil servants lack political training and understanding of the importance of their role, which contributes to corruption. Ethics, according to the authors, is a key tool for strengthening institutions and regaining public trust. The research evaluated the impact of a professional ethics training program on public servants, finding significant improvements in their ethical knowledge and behavior. It concludes that, although ethics will not solve all corruption problems, it is an indispensable component for strengthening accountability and justice in public administration. It underscores the need to implement continuous training programs that promote ethical values as part of a strategy to improve efficiency and transparency in public institutions.

Recognizing the discipline category of the abstract text is of great significance for automatic text recommendation and knowledge mining. Therefore, this study obtained the abstract text of social science and natural science in the Web of Science 2010-2020, and used the machine learning model SVM and deep learning model TextCNN and SCI-BERT models constructed a discipline classification model. It was found that the SCI-BERT model had the best performance. The precision, recall, and F1 were 86.54%, 86.89%, and 86.71%, respectively, and the F1 is 6.61% and 4.05% higher than SVM and TextCNN. The construction of this model can effectively identify the discipline categories of abstracts, and provide effective support for automatic indexing of subjects.