Abstract:Transparency gaps in agricultural supply chains disproportionately affect smallholder coffee producers who receive minimal value from premium specialty markets. This research designed and piloted a blockchain-based traceability platform across three coffee cooperatives in eastern Uganda, involving 420 smallholder farmers. The system recorded provenance data from farm-level harvesting through processing, transport, and export using low-cost mobile interfaces and QR code integration. Over a 12-month pilot period, participating farmers received 18 to 26 percent higher prices compared to conventional marketing channels due to verified origin certification. Smart contract automation reduced payment settlement times from 45 days to 72 hours. Technical evaluation demonstrated platform scalability handling 15,000 daily transactions with 99.7 percent uptime. The framework offers a replicable model for enhancing value chain equity in developing agricultural economies.
Abstract:Microplastic pollution in remote freshwater ecosystems has emerged as a critical environmental concern, yet baseline data for Patagonian lakes remains scarce. This study conducted systematic sampling across 14 glacial lakes in southern Chile, analyzing surface water, sediment, and biota samples during austral summer and winter campaigns. Microplastic concentrations ranged from 0.8 to 12.4 particles per liter in surface waters, with polyethylene and polypropylene fragments comprising 67 percent of identified polymers. FTIR spectroscopy and scanning electron microscopy revealed significant weathering patterns indicative of long-range atmospheric transport rather than local sources. Spatial analysis demonstrated higher concentrations in lakes receiving glacial meltwater, suggesting cryospheric accumulation and release mechanisms. Bioaccumulation assessment in native fish species Galaxias maculatus revealed microplastic ingestion rates correlating with trophic position and feeding behavior.
Abstract:Medieval stone carvings known as khachkars represent an endangered cultural heritage requiring urgent digital documentation. This project employed close-range photogrammetry and structured light scanning to create high-resolution 3D models of 48 khachkars dating from the 9th to 14th centuries across six Armenian monastic complexes. The methodology achieved sub-millimeter geometric accuracy with average point cloud densities exceeding 2.3 million points per square meter. Comparative analysis between photogrammetric and laser scanning outputs demonstrated equivalent accuracy for intricate relief surfaces while significantly reducing field acquisition time. Machine learning-based classification of ornamental motifs identified previously unrecognized stylistic connections between geographically distant carving workshops. The resulting digital archive provides both a preservation resource and a research tool for art historical analysis of medieval Caucasian sculptural traditions.
Abstract:Access to reliable electricity remains a fundamental challenge for remote Melanesian communities where grid extension is economically unfeasible. This study presents an optimization framework for hybrid solar-wind-battery systems tailored to the unique climatic and socioeconomic conditions of Papua New Guinea highlands and coastal regions. Using 15 years of meteorological data and load profiling from 24 off-grid villages, we developed a multi-objective optimization model balancing system reliability, cost minimization, and environmental impact. The optimized configurations achieved 97.2 percent supply reliability at levelized costs 40 percent lower than diesel-only alternatives. Sensitivity analysis revealed that battery storage capacity and solar panel tilt angle were the most influential design parameters. Community ownership models incorporating local maintenance training demonstrated superior long-term sustainability outcomes compared to externally managed installations.
Abstract:Digital exclusion among elderly populations in Pacific Island nations poses significant barriers to accessing essential services increasingly delivered through digital platforms. This mixed-methods study evaluated community-based digital literacy interventions across 12 villages in Fiji, Tonga, and Samoa, involving 186 participants aged 60 and above. The culturally adapted curriculum incorporated storytelling traditions and intergenerational learning pairs, resulting in a 72 percent completion rate compared to 31 percent for standard programs. Post-intervention assessments showed significant improvements in mobile banking navigation, telehealth appointment scheduling, and government portal access. Qualitative analysis highlighted the importance of vernacular language interfaces and family support networks. The findings inform scalable models for bridging the digital divide in geographically dispersed island communities.
Abstract:Antimicrobial resistance represents a critical global health challenge, yet surveillance data from rural primary healthcare settings remains limited. This cross-sectional study analyzed 4,280 bacterial isolates collected from 67 rural clinics across Slovakia, Hungary, and the Czech Republic over a 36-month period. Resistance profiling revealed concerning rates of extended-spectrum beta-lactamase production in Escherichia coli isolates at 28.4 percent, significantly higher than national urban averages. Methicillin-resistant Staphylococcus aureus prevalence reached 19.7 percent in community-acquired infections. Multivariate analysis identified prior antibiotic exposure and agricultural proximity as independent risk factors. The study establishes a replicable surveillance framework for resource-limited rural settings and proposes targeted stewardship interventions to address the identified resistance patterns.
Abstract:Rapid urbanization in sub-Saharan Africa has intensified flood vulnerability due to extensive impervious surface expansion and inadequate drainage systems. This research evaluates green infrastructure solutions including bioswales, permeable pavements, and constructed wetlands across three metropolitan districts in Nairobi. Hydrological modeling using SWMM coupled with GIS-based spatial analysis revealed that strategic green infrastructure deployment reduced peak stormwater runoff by 34 to 51 percent depending on rainfall intensity. Cost-benefit analysis demonstrated favorable long-term economic returns compared to conventional grey infrastructure approaches. Community engagement surveys indicated strong public support when interventions incorporated local ecological knowledge. These findings provide evidence-based guidelines for integrating nature-based solutions into urban planning frameworks across rapidly growing African cities.
Abstract:This study develops adaptive machine learning models to predict crop yield variability across semi-arid agricultural zones. Using satellite-derived vegetation indices, soil moisture data, and historical weather records from 2010 to 2024, we trained ensemble models combining random forests, gradient boosting, and neural networks. The models were validated against actual yield data from 340 smallholder farms in southeastern Bangladesh. Results demonstrate that the adaptive ensemble approach achieved 87.3 percent prediction accuracy, outperforming traditional regression models by 23 percent. Seasonal precipitation timing was identified as the strongest predictor, followed by soil organic carbon content. The framework enables early warning systems for crop failure, supporting proactive intervention strategies for vulnerable farming communities in climate-sensitive regions.
Abstract:Abstract Early childhood is a critical developmental period during which the foundations of children�s emotional, behavioral, and social development are established. During this period, the limits provided by parents play a decisive role in fostering children�s sense of security, autonomy development, and the emergence of self-regulation skills. However, the concept of limit setting in the literature is predominantly addressed within the contexts of discipline, parenting styles, or problem behaviors, while comprehensive, relational, and culturally sensitive theoretical frameworks remain limited. This study is a narrative review that examines the concept of limit setting in early childhood through its theoretical foundations, developmental functions, maternal and paternal roles, coparenting dynamics, and cultural context. Within the scope of the review, the functions of limit setting in child development are discussed based on attachment theory, psychosocial development perspectives, and self-regulation frameworks, with particular emphasis on the quality, consistency, and relational context of limits. The findings indicate that limit setting should not be conceptualized merely as a practice aimed at controlling children�s behavior; rather, it constitutes a fundamental parenting mechanism that supports secure attachment and facilitates the development of self-control and social adjustment. Furthermore, the review highlights the critical importance of considering maternal and paternal roles together and adopting culturally sensitive approaches to limit setting in promoting healthy development during early childhood. By distinguishing limit setting from discipline-oriented approaches, this review aims to reposition it within a developmental guidance and relationship-based parenting perspective.
Abstract:This study offers extensive bibliometric analysis of research pertaining to flood disaster management. The focus of this study is specifically on emergency tools and evacuation strategies. Using data extracted from the Scopus database on countries, keywords, highly cited publications, and trending research topic, the bibliometric software VOSviewer has been employed to evaluate bibliographic entries. A total of 639 publications were retrieved using the Scopus database. The finding reveals that the Unites States, China, and Australia were the top contributors. This is because they are all at risk of floods and have strong research capabilities. Keyword co-occurrence mapping found 73 keywords grouped into seven thematic clusters. This cluster covers strategic policy frameworks, operational decision-making, technological innovations, environmental modeling, and social resilience. The analysis of the co-authorship was performed with the help of two main collaboration networks, namely predominantly Italian and international partnerships. The system features robust intra-cluster connections and bridging authors who enable cross-border knowledge exchange. The findings from this bibliometric analysis reveal that flood disaster research is multidisciplinary, combining engineering, technology, environmental sciences, and social perspective to make the world more flood resistant. This work offers a data-driven summary to help set research priorities for the future. Apart from that it also encourages people to work together to get ready for floods.