Early warning systems (EWS) are crucial for disaster risk reduction, providing timely and reliable information to communities and authorities for proactive mitigation. Traditional methods, such as weather stations, river gauges, and seismic networks, have limitations in spatial coverage, real-time data availability, and precursor signal detection. Recent technological advancements have enhanced EWS by integrating remote sensing data from satellites, airborne platforms, and ground-based sensors, enabling real-time monitoring of phenomena like wildfires, volcanic activity, and landslides. The Internet of Things (IoT) and crowdsourced data from social media, mobile apps, and citizen reports have further improved situational awareness and response times, complementing traditional systems. Increased computational power has enabled the development of sophisticated models, such as numerical weather prediction and seismic hazard models, which predict disaster impacts more accurately. Despite these advancements, challenges remain in data interoperability, resilient communication infrastructure, and delivering clear, actionable alerts to at-risk populations. Future EWS will likely become more data-driven and interconnected, leveraging artificial intelligence, big data analytics, and IoT. Collaboration among governments, academic institutions, and local communities is essential to building robust, inclusive EWS that save lives and reduce the economic impact of disasters.

This study assesses the sustainability of Uganda's carbon markets in the context of climate-smart agricultural practices with the aim of aligning them with sustainable development goals. The research emphasizes integrating dimensions of sustainable development to proactively address food security and climate issues. Climate-smart agricultural practices that support the efficiency of small-scale farming enable farmers to generate income through the sale of carbon-related environmental services such as reduced greenhouse gas emissions and carbon sequestration. While these practices contribute to the resilience of smallholder farmers' livelihoods, challenges arise from large project volumes with low transaction costs, resulting in insufficient carbon revenues for local communities. Furthermore, limited methods and complex procedures hinder progress. The study recommends involving national or international organizations to bridge the gap between farmer groups and the carbon market, with a focus on government policy and private sector collaboration to incentivize environmental services. In summary, establishing sustainable, climate-smart agricultural links to the carbon market can bring co-benefits including income diversification, poverty reduction and biodiversity conservation.

Invasive alien species pose a serious threat to the world’s ecosystems and livelihoods. This review aimed to investigate the negative and positive impacts of Prosopis juliflora (Sw.) DC on ecosystems in Kenya and Ethiopia. The bibliographic analysis highlighted that Prosopis juliflora was introduced to Kenya and Ethiopia to tackle desertification, ensure the self-sufficiency of wood products, and conserve water and soil in semi-arid areas. Years later, this species has turned invasive; although the communities in infested areas have realized some benefits from this tree such as obtaining timber, charcoal, firewood, shelter, and livestock feed from its pods; the negative impacts of this tree have far outweighed the positives. Notably, this invasive plant has significantly impacted agricultural and livestock productivity by invading pasturelands and farmlands. For instance, the negative health implications for livestock significantly reduce their productivity. Similarly, this plant has reduced the diversity of the native trees, herbaceous, and grasses because of its ability to outcompete them. Control methods such as biological, mechanical, chemical, and control by utilization have been tried but none have so far been effective in controlling this invasive plant. Our results showed that Prosopis juliflora is a serious invader that has a huge potential to invade the arid and semi-arid lands of Kenya and Ethiopia. Therefore, stakeholders at all levels need to implement integrated management strategies to reduce the spread and the negative impacts of this species.

The agricultural sector is a cornerstone of economic development and food security in Sub-Saharan Africa (SSA). However, the region's agricultural supply chains face persistent challenges, including inefficiencies, lack of transparency, and limited traceability. These issues result in high post-harvest losses, unfair pricing for farmers, and compromised consumer trust. Blockchain technology, with its decentralized, immutable, and transparent ledger system, has emerged as a promising solution to address these challenges. This review explores the application of blockchain technology in improving efficiency and transparency within agricultural supply chains in SSA. By integrating blockchain with smart contracts, Internet of Things (IoT) devices, and real-time data sharing, stakeholders can automate processes, enhance traceability, and reduce transaction costs. For instance, blockchain-based platforms can provide farmers with direct market access, ensuring fairer prices and reducing the influence of intermediaries. Moreover, the immutable nature of blockchain ensures the credibility of supply chain data, fostering consumer trust and facilitating compliance with international quality standards. Despite its potential, blockchain adoption in SSA faces significant barriers, including high implementation costs, inadequate infrastructure, and limited technical expertise. Social challenges, such as resistance to change and low awareness of blockchain benefits, also hinder widespread adoption. To unlock blockchain’s potential, the study emphasizes the need for affordable, scalable solutions and supportive policy frameworks tailored to the unique context of SSA. This review highlights the transformative potential of blockchain in addressing critical inefficiencies and transparency gaps in SSA's agricultural supply chains. It underscores the importance of collaborative efforts among governments, private sector stakeholders, and international organizations to drive adoption and foster sustainable agricultural development in the region. By leveraging blockchain, SSA can achieve more equitable and resilient supply chains, contributing to economic growth and food security.

Aim: To adapt to changing climate, farmers should transform their farming practices and adopt various methods that sustainably increase agricultural productivity and resilience. This study assessed climate-smart agricultural practices adopted and the determinants influencing adoption among...

The healthcare sector is witnessing significant development in many aspects thanks to the effects of artificial intelligence or software, which has turned out to be the centre of attraction all over the world. This is evidence of a simple development in acquiring deep knowledge of the methods and areas in which they are used. Face detection, voice recognition, autonomous use, the defence industry, the security industry, and other fields may be displayed as examples that help complete tasks. This article surveys the impact of deep learning methods and practices in the medical device industry, and we also examine the distribution of multi-year data. It is divided into six categories: healthcare, big data and wearable technologies, biomedical code, image processing, diagnostics, and the Internet of Medical Things. As a result, the medical device industry has grown in recent years through deep learning techniques and the use of most research related to diagnosis and image processing.