Pavement structures are one of the most critical civil infrastructures for the socio-economic development of communities. However, pavement construction demands an elevated financial budget and generates large amounts of environmental impacts. Accordingly, the new trends in daily engineering practices have integrated sustainability criteria verification into traditional pavement design procedures. Thus, this research explores the sustainability implications of asphalt pavement incorporating a Cement-Treated Base (CTB) and Recycled Concrete Aggregate (RCA) within the local context of a Global South country. The environmental and economic performances of four different types of asphalt structures were assessed, each differing in how the CTB is employed. These structures include conventional flexible pavement, semi-rigid pavement, inverted base pavement, and simple composite pavement. Furthermore, each structure is evaluated under four varying contents of coarse RCA (i.e., 0%, 15%, 30%, and 45%) in their asphalt mixtures. This approach results in a comprehensive analysis spanning 16 unique scenarios, providing valuable insights into the interplay between RCA content and CTB inclusion for sustainable infrastructure development. It is important to highlight that the Life-Cycle Assessment and Life-Cycle Cost Analysis methodologies were implemented to perform the environmental and economic inspections, respectively. Overall, this investigation demonstrates that although pavement structures comply with mechanistic design standards, they can yield significantly different cost effectiveness and environmental burdens from each other. Therefore, executing a sustainability-related appraisal is essential for accomplishing definitive infrastructure designs. Consequently, this research effort is expected to be used by stakeholders (e.g., civil engineers, designers, and governmental agencies) to support data-driven decision making in the road infrastructure industry.

Worldwide, the healthcare industry produces massive quantities of medical waste (MW), most of which is incinerated, releasing large quantities of dioxins, mercury, and other pollutants. Despite this, only a limited number of studies have explored the incorporation of MW into construction materials, with a special focus on cement-based construction materials (CB-CMs). However, to the best of the authors’ knowledge, no existing review formally structures, summarizes, correlates, and discusses the findings of previous studies on MW in CB-CMs to encourage further research and applications of this promising alternative. Therefore, the added value of this study lies in providing an innovative and critical analysis of existing research on the use of MW in CB-CMs, consolidating and evaluating dispersed findings through a systematic literature review, enhancing understanding of the topic, and identifying knowledge gaps to guide future research. A robust systematic literature review was conducted, encompassing 40 peer-reviewed research articles, retrieved from the Web of Science Core Collection database. The methodology involved a three-stage process: a descriptive analysis of the included articles, the identification and synthesis of key thematic areas, and a critical evaluation of the data to ensure a rigorous and systematic report. The selection criteria prioritized peer-reviewed research articles in English with full text availability published in the last 7 years, explicitly excluding conference papers, book chapters, short reports, and articles not meeting the language or accessibility requirements. The results indicate that the influence of MW in CB-CM varies significantly. For example, while the incorporation of face masks as fiber reinforcement in concrete generally enhances its mechanical and durability properties, the use of gloves is less effective and not always recommended. Finally, it was found that further research is needed in this field due to its novelty.

Soil–water management is fundamental to plant ecophysiology, directly affecting plant resilience under both anthropogenic and natural stresses. Understanding Agricultural Soil–Water Management Properties (ASWMPs) is therefore essential for optimizing water availability, enhancing harvest resilience, and enabling informed decision-making in intelligent irrigation systems, particularly in the face of climate variability and soil degradation. In this regard, the present research develops predictive models for ASWMPs based on the grain size distribution and dry bulk density of soils, integrating both traditional mathematical approaches and advanced computational techniques. By examining 900 soil samples from the NaneSoil database, spanning diverse crop species (Avena sativa L., Daucus carota L., Hordeum vulgare L., Medicago sativa L., Phaseolus vulgaris L., Sorghum vulgare Pers., Triticum aestivum L., and Zea mays L.), several predictive models are proposed for three key ASWMPs: soil-saturated hydraulic conductivity, field capacity, and permanent wilting point. Mathematical models demonstrate high accuracy (71.7–96.4%) and serve as practical agronomic tools but are limited in capturing complex soil–plant-water interactions. Meanwhile, a Deep Neural Network (DNN)-based model significantly enhances predictive performance (91.4–99.7% accuracy) by uncovering nonlinear relationships that govern soil moisture retention and plant water availability. These findings contribute to precision agriculture by providing robust tools for soil–water management, ultimately supporting plant resilience against environmental challenges such as drought, salinization, and soil compaction.

Phenolic-rich extracts from Satureja montana were evaluated before and after diazomethane treatment to determine how chemical derivatization influences their antioxidant capacity. Native and modified extracts were compared experimentally by measuring total phenolic content, ferric reducing antioxidant power (FRAP), and Fe²⁺-chelating ability. EN1 exhibited the highest concentration of phenolic compounds, reaching 1278.54 mmol/g, whereas EM2 retained only 1.99 mmol/g. In the FRAP assay, reducing power followed the order EN1 (9.36) > EN2 (3.72) > EM2 (2.08), with EM2 still exceeding caffeic, chlorogenic, and ferulic acids. In contrast, the modified extracts showed superior metal chelating capacity, with EM1 and EM2 displaying IC₅₀ values of 0.70 and 0.82 mg/mL, respectively, both markedly lower than those of the native extracts and the pure standards. To rationalize these differences, a DFT study was performed at the B3LYP/6-311++G(d,p) level, examining 18 proposed phenolic acids and their methylated derivatives associated with the extracts. All methylation reactions were thermodynamically favorable, particularly for compounds 18 (−57.10 kcal/mol), 16 (−53.96), 6 (−53.34), and 3, 9, and 11 (−52.71). Solvent effects were found to be structure-dependent: caffeic acid showed BDE values of 72.29, 73.59, and 74.43 kcal/mol in the gas phase, water, and benzene, respectively, whereas syringic acid displayed values of 80.44, 77.09, and 80.65 kcal/mol under the same conditions. Likewise, the ionization potential of caffeic acid decreased from 180.09 kcal/mol in the gas phase to 133.26 kcal/mol in water and 154.22 kcal/mol in benzene. Among all analyzed species, methyl 3,4-dihydroxycinnamate exhibited the lowest BDE (71.60 kcal/mol) as well as the most favorable ΔG°r toward HOO• (−11.06 kcal/mol).