With the purpose of knowing the phytosocilogy of weeds associated to a carrot crop (Daucus carota L.) under conditions of the municipalities of Ventaquemada and Jenesano-Boyacá, one lot per municipality destined to carrot cultivation was selected and a W-shaped layout was made covering an area of 500 m². Relative density, relative frequency, relative dominance and the importance value index (IVI) were calculated, as well as the Alpha and Beta diversity indices for the sampled areas. A total of 6 families and 11 species were counted, of which 63.64% were represented by annual plants and 36.36% by perennial plants. The class Liliopsida (Monocotyledon) was represented by the Poaceae family. The Magnoliopsida class (Dicotyledon) was represented by the following families: Asteraceae, Brassicaceae, Boraginaceae, Leguminosaceae, Polygonaceae, the last one being the one with the highest number of species. The species R. crispus and P. nepalense were the ones with the highest values of Importance Value Index (IVI) with 0.953 and 0.959, respectively. According to the Shannon-Wiener diversity and Simpson’s dominance indices, the evaluated areas presented a low species diversity and a high probability of dominant species. The results obtained can serve as a basis and tool for carrot growers in the evaluated areas to define management plans for the associated weeds and thus optimize yields in this crop.

Problem: in recent years, new studies have been published on biological effects of strong static magnetic fields and on thermal effects of high-frequency electromagnetic fields as used in magnetic resonance imaging (MRI). Many of these studies have not yet been incorporated into current safety recommendations. Method: scientific publications from 2010 onwards on the biological effects of static and electromagnetic fields of MRI were searched and evaluated. Results: new studies confirm older work that has already described effects of static magnetic fields on sensory organs and the central nervous system accompanied by sensory perception. A new result is the direct effect of Lorentz forces on ionic currents in the semicircular canals of the vestibular organ. Recent studies on thermal effects of radiofrequency fields focused on the development of anatomically realistic body models and more accurate simulation of exposure scenarios. Recommendation for practice: strong static magnetic fields can cause unpleasant perceptions, especially dizziness. In addition, they can impair the performance of the medical personnel and thus potentially endanger patient safety. As a precaution, medical personnel should move slowly in the field gradient. High-frequency electromagnetic fields cause tissues and organs to heat up in patients. This must be taken into account in particular for patients with impaired thermoregulation as well as for pregnant women and newborns; exposure in these cases must be kept as low as possible.

This paper proposes a floating-interest-rate infrastructure bond, where the interest of a government bond is paid to investors during the period of construction and the early period of operation. Unlike the usual government bond, which provides a fixed interest rate, the proposed floating-interest-rate infrastructure bond pays a floating interest, the rate of which depends on spillover tax revenues. Effective infrastructure projects have a positive effect on the economic growth of a region, known as the spillover effect. When user charges and the return from spillover tax revenues are below the fixed rate of the government bond, the interest rate will equal to the fixed rate of the government bond. In this case, investors in the infrastructure will receive interest on the government bond at the minimum rate. As the spillover effect of the infrastructure increases, the rate of return for infrastructure investment will become greater than the fixed rate of the government bond. The success of the floating-interest-rate infrastructure bond depends on the spillover effect and on transparency and accountability. Policy recommendations are provided in this paper on how to increase the spillover effect and improve transparency and accountability. 

The integration of Big Earth Data and Artificial Intelligence (AI) has revolutionized geological and mineral mapping by delivering enhanced accuracy, efficiency, and scalability in analyzing large-scale remote sensing datasets. This study appraisals the application of advanced AI techniques, including machine learning and deep learning models such as Convolutional Neural Networks (CNNs), to multispectral and hyperspectral data for the identification and classification of geological formations and mineral deposits. The manuscript provides a critical analysis of AI’s capabilities, emphasizing its current significance and potential as demonstrated by organizations like NASA in managing complex geospatial datasets. A detailed examination of selected AI methodologies, criteria for case selection, and ethical and social impacts enriches the discussion, addressing gaps in the responsible application of AI in geosciences. The findings highlight notable improvements in detecting complex spatial patterns and subtle spectral signatures, advancing the generation of precise geological maps. Quantitative analyses compare AI-driven approaches with traditional techniques, underscoring their superiority in performance metrics such as accuracy and computational efficiency. The study also proposes solutions to challenges such as data quality, model transparency, and computational demands. By integrating enhanced visual aids and practical case studies, the research underscores its innovations in algorithmic breakthroughs and geospatial data integration. These contributions advance the growing body of knowledge in Big Earth Data and geosciences, setting a foundation for responsible, equitable, and impactful future applications of AI in geological and mineral mapping.

The Middle East and North Africa (MENA) region faces unique challenges and opportunities in integrating sustainability into sovereign credit assessments. This research study examines environmental, social, and governance (ESG) factors embedded in the lending policies of jurisdictional institutions in MENA. By analyzing existing literature and case studies, we identify key drivers and barriers to ESG integration in sovereign lending. Our findings suggest a growing recognition of sustainability’s importance in financial stability and credit, driven by global climate guarantees and local socio-economic development. However, challenges such as data availability, regulatory frameworks, and market acceptance persist. This paper provides an overview of current practices, highlights best practices, and offers recommendations to enhance ESG integration in sovereign debt reviews in the MENA region. The study concludes that a robust ESG framework is necessary to accurately reflect the long-term risks and opportunities associated with sovereign debt, ultimately contributing to sustainable economic growth regionally.

The development of the times and the progress of society have put forward new requirements for the conduct of party building work. Only by adhering to innovative ideas, continuously adjusting and scientifically planning the mode of party building work, can a new and systematic guidance system for party building be constructed, so that the conduct of party building work in universities presents a new development state and mode. Based on the influence of the information technology environment and the guidance of the spirit of the 20th National Congress, this article explores and analyzes the innovative reform of party building work in universities in the new era. From different perspectives such as introducing advanced technology and innovative party building work concepts, it systematically explores the innovative planning measures for party building work, striving to build a new organizational system for party building in universities, and scientifically optimize the value and effectiveness of party building work in universities.