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In West Africa, the number of people facing food crises increases each year in both rural and urban areas, due to interdependent factors. The city of Grand Lome in Togo faces an increasingly large population that must ensure access to food, which it hardly produces anymore, because of the establishment of housing and infrastructure. In addition, the increase in the price of food products in this city further weakens the purchasing power of city dwellers in the context of poverty. The objective of this article is to determine the state of food and nutritional security of households in Grand Lome. The methodology adopted is based on documentary research and field surveys. A total of 310 households were interviewed on questions allowing the construction of indicators of food and nutritional security. The results show that despite the availability of food in urban markets, the food situation of households in Grand Lome is not very good. Nearly 49% of households do not have good dietary diversity, and 48% have adopted stress and crisis strategies to access food. Similarly, in Grand Lome, the prevalence of global acute malnutrition is 2.6% of children under 59 months. [ABSTRACT FROM AUTHOR]

This paper investigates rural mobility in the Global South using a participatory GIS approach to address the lack of mobility data that hampers sustainable planning to support rural development and resilience. Limited rural mobility due to poor infrastructure and financial constraints hinders social and economic activities, impeding development. The study aims to explore the socio-economic impacts of limited mobility, identify software needs for data-scarce environments, and map daily mobility patterns. Fieldwork was conducted in Kenya (2022) and Nepal (2023), collecting geographic data related to mobility. The methodology included community engagement and digital mapping using the QField app for precise data collection. The study highlights the use of participatory GIS to fill data gaps, enabling more accurate mobility assessments. Community engagement revealed gender-specific mobility patterns, with women facing particular challenges in daily activities. The study emphasizes the need for adaptable data models to reflect community-specific mobility needs and the integration of qualitative insights to propose effective and sustainable mobility solutions. This research contributes to understanding rural mobility in the Global South and demonstrates the effectiveness of participatory GIS in overcoming data scarcity and enhancing mobility analysis. [ABSTRACT FROM AUTHOR]

This study leverages a Discrete Event Simulation (DES) model to optimize the sweet potato supply chain in Zimbabwe, focusing on production, distribution, and market dynamics under varying climate conditions. The integration of climate data into the simulation model reveals significant insights into the resilience of different sweet potato varieties, particularly highlighting the suitability of yellow-skinned sweet potatoes for harsh climates due to their high resilience and drought resistance. However, market preferences still favor white-skinned varieties despite their vulnerability to climate extremes. The DES model identifies key bottlenecks, particularly in cultivation and transportation, that hinder supply chain efficiency. To address these challenges, the study emphasizes the importance of targeted interventions, such as improving access to irrigation, strengthening pest management, and adopting community-based resource-sharing approaches. These strategies are critical for enhancing both the resilience and efficiency of the supply chain. Additionally, the study highlights the urgent need for adaptive strategies to mitigate the effects of drought on agricultural productivity, especially in regions that heavily rely on crops like sweet potatoes. Overall, this research offers strategic insights for policymakers and stakeholders aiming to improve food security and agricultural productivity in Zimbabwe, as well as in other countries with similar climate challenges. [ABSTRACT FROM AUTHOR]

Climate change is a global phenomenon impacting ecosystems, economies, and livelihoods. This research carried out in Bol in the Lake Province of Chad, a region heavily affected by climate change, aims to analyze the gender-differentiated impacts of this phenomenon. It was carried out using the rapid analysis and participatory planning (RAPP) method and structural analysis for social systems (SAS2). Meteorological and socioeconomic data were collected through interviews, household surveys, and focus groups. The results indicate variability in rainfall, with a slight downward trend and an increase in temperature. The women identified an increase in the cost of living, human and material losses, warmer housing, and health problems as socioeconomic socioeconomic consequences of climate change. Their coping strategies include community self-help, humanitarian aid, and welfare activities. Obstacles to full participation in the search for solutions include access to education, low decision-making power, and political representation. This research enriches our understanding of the interactions between gender, climate change, adaptation, and inclusive policy importance. [ABSTRACT FROM AUTHOR]

The advancement to Urban 4.0 requires urban digitization and predictive maintenance of infrastructure to improve efficiency, durability, and quality of life. This study aims to integrate intelligent technologies for the predictive maintenance of photovoltaic panel systems, which serve as essential smart city renewable energy sources. In addition, we employ vision transformers (ViT), a deep learning architecture devoted to evolving image analysis, to detect anomalies in PV systems. The ViT model is pre-trained on ImageNet to exploit a comprehensive set of relevant visual features from the PV images and classify the input PV panel. Furthermore, the developed system was integrated into a web application that allows users to upload PV images, automatically detect anomalies, and provide detailed panel information, such as PV panel type, defect probability, and anomaly status. A comparative study using several convolutional neural network architectures (VGG, ResNet, and AlexNet) and the ViT transformer was conducted. Therefore, the adopted ViT model performs excellently in anomaly detection, where the ViT achieves an AUC of 0.96. Finally, the proposed approach excels at the prompt identification of potential defects detection, reducing maintenance costs, advancing equipment lifetime, and optimizing PV system implementation. [ABSTRACT FROM AUTHOR]

Drought monitoring is a critical environmental challenge, particularly in regions where irrigated agricultural intensification and urban expansion pressure water resources. This study assesses the impact of these activities on drought dynamics in Morocco's Oum Er-Rbia (OER) watershed from 2002 to 2022, using the newly developed Watershed Integrated Multi-Drought Index (WIMDI), through Google Earth Engine (GEE). WIMDI integrates several drought indices, including SMCI, ESI, VCI, TVDI, SWI, PCI, and SVI, via a localized weighted averaging model (LOWA). Statistical validation against various drought-type indices including SPI, SDI, SEDI, and SMCI showed WIMDI's strong correlations (r-values up to 0.805) and lower RMSE, indicating superior accuracy. Spatiotemporal validation against aggregated drought indices such as VHI, VDSI, and SDCI, along with time-series analysis, confirmed WIMDI's robustness in capturing drought variability across the OER watershed. These results highlight WIMDI's potential as a reliable tool for effective drought monitoring and management across diverse ecosystems and climates. [ABSTRACT FROM AUTHOR]

African urban agriculture (UA) has garnered attention for its contributions to food security and socio-economic improvement. However, its impact on the psychological well-being of farmers has received minimal focus. This study explores the psychosocial effects of UA by surveying 733 farmers in Dar es Salaam and Greater Lomé. Utilizing the Mental Health Continuum–Short Form (MHC-SF) and bespoke questionnaires, our research evaluates the emotional benefits of urban farming. Findings from regression analyses and spatial assessments conducted using Python and QGIS 3.32.2-Lima indicate significant variations in UA-related happiness across different city zones, with peripheral farmers experiencing greater satisfaction than their urban counterparts. Notably, female farmers reported higher levels of happiness, underscoring UA's potential to empower women. This study advocates for the integration of UA into urban planning frameworks to foster psychologically beneficial urban environments. [ABSTRACT FROM AUTHOR]

Mobility practices in Cameroon have changed considerably due to the rapid spread of COVID-19. Based on data collection in Yaoundé and Douala, the country’s main cities, which combined 878 questionnaires, 11 interviews and direct observation, this research analysed the mobility practices of city dwellers in a crisis context. Its results reveal social coping mechanisms in the face of the fear of contracting COVID-19. The context was marked by a series of aggravating, structural and cultural factors that influenced the choice of modes of daily travel or the option to remain confined. Four types of modal habits were identified, each responding to individual modal logics during the pandemic: users sensitive to the cost of transport, phobic users, local or short-distance users and exclusive circumstantial motorists.

Water distribution systems (WDSs) are complex networks with numerous interconnected junctions and pipes. The robustness and reliability of these systems are critically dependent on their network structure, necessitating detailed analysis for proactive leak detection to maintain integrity and functionality. This study addresses gaps in traditional WDS analysis by integrating hydraulic measures with graph theory to improve sensitivity analysis for leak detection. Through case studies of five distinct WDSs, we investigate the relationship between hydraulic measures and graph theory metrics. Our findings demonstrate the collective impact of these factors on leak detection and system efficiency. The research provides enhanced insights into WDS operational dynamics and highlights the significant potential of graph theory to bolster network resilience and reliability. [ABSTRACT FROM AUTHOR]

More and more cities in Southern Africa are struggling to manage their waste in a context of rapid urbanisation and increasing poverty. In the Cameroon's largest city, Yaoundé, managing household waste is a growing concern. The public and the authorities cast blame on each other, and the actions taken by each party far from guarantee an efficient management of household waste, which litters the streets. Considering the above, this paper analyses the socio-political practices of stakeholders and their influence on household waste management in Yaoundé. Based on a qualitative survey that combined both a literature review and interviews, the research analysed the challenges related to household waste management with regard to the economy, the environment, and public health. In addition, a cartographic survey using KoboToolbox was conducted in all seven municipalities to analyse the geographical distribution of the waste areas, their size, and their status within the city organizational framework. In total, 264 waste dumps were collected, of which 110 were formal waste using a waste bin of varying size. Social constructivism, stakeholder theory, and strategic analysis were mobilized to analyse the urban waste governance in Yaoundé. Thus, the poor quality of household waste management in Yaoundé was explained using political, economic, sociocultural, and environmental parameters. The social practices and dynamics of the stakeholders generate undesirable consequences that hinder the achievement of the Sustainable Development Goals (SDGs). By combining social science and engineering methods, this research aims to demonstrate that the shortcomings of waste governance in Yaoundé are both a collective (authorities/public powers) and individual (citizens) matter. [ABSTRACT FROM AUTHOR]