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  • Rural Digital Europe

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  • Open Access
    Authors: 
    Abraham Ninian Ejin; Hoe Tung Yew; Mazlina Mamat; Farrah Wong; Ali Chekima; Seng Kheau Chung;
    Publisher: Zenodo

    <span lang="EN-US">The coronavirus disease (COVID-19) outbreak has led to many infected worldwide and has become a global crisis. COVID-19 manifests in the form of shortness of breath, coughing and fever. More people are getting infected and healthcare systems worldwide are overwhelmed as healthcare workers become exhausted and infected. Thus, remote monitoring for COVID-19 patients is required. An internet of things (IoT) based real-time health monitoring system for COVID-19 patients was proposed. It features monitoring of five physiological parameters, namely electrocardiogram (ECG), heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2) and body temperature. These vitals are processed by the main controller and transmitted to the cloud for storage. Healthcare professionals can read real-time patient vitals on the web-based dashboard which is equipped with an alert service. The proposed system was able to transmit and display all parameters in real-time accurately without any packet loss or transmission errors. The accuracy of body temperature readings, RR, SpO2 and HR, is up to 99.7%, 100%, 97.97% and 98.34%, respectively. Alerts were successfully sent when the parameters reached unsafe levels. With the proposed system, healthcare professionals can remotely monitor COVID-19 patients with greater ease, lessen their exposure to the pathogen, and improve patient monitoring.</span>

  • Open Access English
    Authors: 
    Mathenge, Mwehe;
    Publisher: Proefschrift Maken

    Addressing the intertwined challenges of low agricultural productivity, food insecurity and non-market participation by poor smallholder households is a complex undertaking that would require an integrated multidisciplinary approach and spatially integrated agriculture policies. However, many of the agricultural policies in LMICs are not usually sufficiently spatially integrated and are deficient in multi-level, multi-sectoral, and multi-actor integration. With the increasing embedding of agricultural production and food insecurity challenges in local spatial complexity, and, given the multidimensional nature of food security, agriculture policies should be spatially sensitive to the spatial variation of food insecurity and spatial heterogeneity of territorial resources. By mapping the spatial patterns of households’ food inequalities, policy planners can better understand the local causation of low agriculture productivity and food insecurity. This can enable policymakers and relevant stakeholders to spatially target deprived areas and develop appropriate, place-based intervention strategies and policies. Using Geographic Information Systems (GIS) and remote sensing technologies to map local spatial patterns of food insecurity offers important insights into the spatial disparities of the territorial dimension of food security and causes of agriculture productivity and poverty. With increasing recognition that place-specific features and territorial specificities strongly influence agriculture activities and food security outcomes, there is a need for place-specific policies and spatial-based interventions that are grounded in the local reality and informed by the local needs of smallholders. However, traditionally based “top-down” and sector-specific agriculture policies often designed at the national level, do not sufficiently take into account the spatial heterogeneity of territories. Thus, they would not offer sufficient conditions to address the multi-dimensional causes of low agriculture productivity and food insecurity. This thesis presents a combination of GIS-based indicators and spatially explicit methodologies to offer a more viable diagnostic tool for mapping local spatial interactions and increases the effectiveness of unearthing deep-rooted causes of food insecurity. This provides policymakers and local governments with an evidence-based approach in the application of remedy policies for prioritization of resources, spatial targeting of resources, and the design of location-specific interventions in improving the sustainability of smallholder systems. Well-articulated and coordinated spatial targeted development policies that tap into the resource heterogeneity of territories with geographic specificities while enhancing the diversity of particular regions would create the prerequisites required to develop local and sustainable smallholder systems while enhancing their sustainability. With increasing global food insecurity, poverty, climate change, and global food supply chains crisis brought about by the covid-19 pandemic, and the Russia-Ukraine war, there is a need for LMICs to shift their dependency on globalized agri-food value chains and instead focus more on the development of localized agribusiness value chains. In this regard, the development of local smallholder agribusiness value chains should become an urgent public policy priority, especially in LMICs that suffer from a perpetual food crisis. Addressing complex food security problems will call for the adoption of transdisciplinary, farmers-led, and spatially-explicit approaches that integrate a diversity of local factors, societal actors, and institutions in knowledge co-sharing and co-creation to find lasting solutions to complex food production problems. Now and in the future, GIS and RS technologies will even become more important in the development of spatially integrated agriculture policies to improve sustainable agricultural practices. In addition, the spatialization of agriculture policies will go a long way in supporting spatially integrated solutions to complex problems facing smallholder agricultural systems.

  • Publication . Doctoral thesis . 2022
    Open Access English

    Addressing the intertwined challenges of low agricultural productivity, food insecurity and non-market participation by poor smallholder households is a complex undertaking that would require an integrated multidisciplinary approach and spatially integrated agriculture policies. However, many of the agricultural policies in LMICs are not usually sufficiently spatially integrated and are deficient in multi-level, multi-sectoral, and multi-actor integration. With the increasing embedding of agricultural production and food insecurity challenges in local spatial complexity, and, given the multidimensional nature of food security, agriculture policies should be spatially sensitive to the spatial variation of food insecurity and spatial heterogeneity of territorial resources. By mapping the spatial patterns of households’ food inequalities, policy planners can better understand the local causation of low agriculture productivity and food insecurity. This can enable policymakers and relevant stakeholders to spatially target deprived areas and develop appropriate, place-based intervention strategies and policies. Using Geographic Information Systems (GIS) and remote sensing technologies to map local spatial patterns of food insecurity offers important insights into the spatial disparities of the territorial dimension of food security and causes of agriculture productivity and poverty. With increasing recognition that place-specific features and territorial specificities strongly influence agriculture activities and food security outcomes, there is a need for place-specific policies and spatial-based interventions that are grounded in the local reality and informed by the local needs of smallholders. However, traditionally based “top-down” and sector-specific agriculture policies often designed at the national level, do not sufficiently take into account the spatial heterogeneity of territories. Thus, they would not offer sufficient conditions to address the multi-dimensional causes of low agriculture productivity and food insecurity. This thesis presents a combination of GIS-based indicators and spatially explicit methodologies to offer a more viable diagnostic tool for mapping local spatial interactions and increases the effectiveness of unearthing deep-rooted causes of food insecurity. This provides policymakers and local governments with an evidence-based approach in the application of remedy policies for prioritization of resources, spatial targeting of resources, and the design of location-specific interventions in improving the sustainability of smallholder systems. Well-articulated and coordinated spatial targeted development policies that tap into the resource heterogeneity of territories with geographic specificities while enhancing the diversity of particular regions would create the prerequisites required to develop local and sustainable smallholder systems while enhancing their sustainability. With increasing global food insecurity, poverty, climate change, and global food supply chains crisis brought about by the covid-19 pandemic, and the Russia-Ukraine war, there is a need for LMICs to shift their dependency on globalized agri-food value chains and instead focus more on the development of localized agribusiness value chains. In this regard, the development of local smallholder agribusiness value chains should become an urgent public policy priority, especially in LMICs that suffer from a perpetual food crisis. Addressing complex food security problems will call for the adoption of transdisciplinary, farmers-led, and spatially-explicit approaches that integrate a diversity of local factors, societal actors, and institutions in knowledge co-sharing and co-creation to find lasting solutions to complex food production problems. Now and in the future, GIS and RS technologies will even become more important in the development of spatially integrated agriculture policies to improve sustainable agricultural practices. In addition, the spatialization of agriculture policies will go a long way in supporting spatially integrated solutions to complex problems facing smallholder agricultural systems.

  • Open Access English
    Authors: 
    Mathenge, Mwehe;
    Publisher: Proefschrift Maken
    Country: Netherlands

    Addressing the intertwined challenges of low agricultural productivity, food insecurity and non-market participation by poor smallholder households is a complex undertaking that would require an integrated multidisciplinary approach and spatially integrated agriculture policies. However, many of the agricultural policies in LMICs are not usually sufficiently spatially integrated and are deficient in multi-level, multi-sectoral, and multi-actor integration. With the increasing embedding of agricultural production and food insecurity challenges in local spatial complexity, and, given the multidimensional nature of food security, agriculture policies should be spatially sensitive to the spatial variation of food insecurity and spatial heterogeneity of territorial resources. By mapping the spatial patterns of households’ food inequalities, policy planners can better understand the local causation of low agriculture productivity and food insecurity. This can enable policymakers and relevant stakeholders to spatially target deprived areas and develop appropriate, place-based intervention strategies and policies. Using Geographic Information Systems (GIS) and remote sensing technologies to map local spatial patterns of food insecurity offers important insights into the spatial disparities of the territorial dimension of food security and causes of agriculture productivity and poverty. With increasing recognition that place-specific features and territorial specificities strongly influence agriculture activities and food security outcomes, there is a need for place-specific policies and spatial-based interventions that are grounded in the local reality and informed by the local needs of smallholders. However, traditionally based “top-down” and sector-specific agriculture policies often designed at the national level, do not sufficiently take into account the spatial heterogeneity of territories. Thus, they would not offer sufficient conditions to address the multi-dimensional causes of low agriculture productivity and food insecurity. This thesis presents a combination of GIS-based indicators and spatially explicit methodologies to offer a more viable diagnostic tool for mapping local spatial interactions and increases the effectiveness of unearthing deep-rooted causes of food insecurity. This provides policymakers and local governments with an evidence-based approach in the application of remedy policies for prioritization of resources, spatial targeting of resources, and the design of location-specific interventions in improving the sustainability of smallholder systems. Well-articulated and coordinated spatial targeted development policies that tap into the resource heterogeneity of territories with geographic specificities while enhancing the diversity of particular regions would create the prerequisites required to develop local and sustainable smallholder systems while enhancing their sustainability. With increasing global food insecurity, poverty, climate change, and global food supply chains crisis brought about by the covid-19 pandemic, and the Russia-Ukraine war, there is a need for LMICs to shift their dependency on globalized agri-food value chains and instead focus more on the development of localized agribusiness value chains. In this regard, the development of local smallholder agribusiness value chains should become an urgent public policy priority, especially in LMICs that suffer from a perpetual food crisis. Addressing complex food security problems will call for the adoption of transdisciplinary, farmers-led, and spatially-explicit approaches that integrate a diversity of local factors, societal actors, and institutions in knowledge co-sharing and co-creation to find lasting solutions to complex food production problems. Now and in the future, GIS and RS technologies will even become more important in the development of spatially integrated agriculture policies to improve sustainable agricultural practices. In addition, the spatialization of agriculture policies will go a long way in supporting spatially integrated solutions to complex problems facing smallholder agricultural systems.

  • Open Access
    Authors: 
    Vér, András; McKee, Annie; Moriarty, John; Honegger, Sandra; O'Dwyer, Tom;
    Publisher: Zenodo
    Project: EC | NEFERTITI (772705)

    NEFERTITI is a ‘Horizon 2020’ project that will run until the end of 2021. It supports on-farm demonstration activities and farmer-to-farmer learning that supports innovation uptake. The name NEFERTITI reflects the full project title: ‘Networking European Farms to Enhance Cross Fertilisation and Innovation Uptake Through Demonstration’. Networking... The project involves ten networks each with a theme. The themes focus on aspects of innovation in livestock production, arable farming, and horticulture. They bring together 45 regional clusters (‘hubs’) of demonstration farmers and people who innovate in agriculture, such as advisors, facilitators, researchers, industry representatives and policy makers. You can Farm: Farm attractiveness Network 10, called ‘Farm Attractiveness’ has the goal of identifying and supporting new people and new pathways into agriculture across Europe. This network supports knowledge exchange demonstration events held on farms and online, with host farmers who are ‘new entrants’ to agriculture. The objective of the demonstration events are to encourage young people to see farming as a future and career that is both worthwhile and worth considering. Network Activities In 2019 a total of 39 events were organised by Network 10 hubs, all of which were either on-farm or in-organisation. In 2020, 31 events were held, 12 of which were held online in response to the Covid-19 pandemic. Online events organised included webinars, panel discussions, and social media ‘takeovers’. One UK virtual event included contributions from four partner countries. The use of social media was critical to the success of the demonstration events, both on-farm, in organisation, or held online. Social media promotion of events attracted young and diverse audiences, and careful use of different platforms appealed to different localities and types of participants (e.g. agricultural college students). For example, the social media ‘takeovers’ involved young farmers directly uploading stories, videos, pictures, and other content to the social media of partner organisations. Videos from the events could be shared via social media to enhance knowledge exchange and links were made available to allow for later viewing. Findings Multimedia use and the use of diverse social media platforms has the potential increase and target audiences. E.g. Instagram events, targeted at young people, also promoted on Facebook and Twitter, including sharing video links. Virtual events have enabled an international dimension to be added to events. E.g. UK webinar featuring contributions from other partners Online events are available for knowledge exchange with those who cannot participate ‘live’. E.g. Webinar recordings are available on YouTube and Instagram highlights of social media takeovers are available on the host channel, and Instagram TV.

  • Open Access Spanish
    Authors: 
    Santamarina Campos, Ana;
    Publisher: Zenodo

    Como en cualquier proyecto de comunicación, el primer paso de todo el proceso ha de ser definir claramente tu público, las personas y entidades a las que, al final de todo el proceso de elaboración y edición, quieres dirigirte… en decir: tus audiencias. Una memoria anual tiene un número de audiencias más amplio que el de los documentos de difusión de información (disclosure) habituales. ¿Cuántas y cuáles son esas audiencias? Por decirlo en cuatro palabras: tus grupos de interés (los famosísimos stakeholder).

  • Open Access English
    Authors: 
    David Christian Rose; Faye Shortland; Jilly Hall; Paul Hurley; Ruth Little; Caroline Nye; Matt Lobley;
    Publisher: Taylor and Francis
    Country: United Kingdom

    Objectives In this paper, we use a UK case study to explore how the COVID-19 pandemic affected the mental health (emotional, psychological, social wellbeing) of farmers. We outline the drivers of poor farming mental health, the manifold impacts of the pandemic at a time of policy and environmental change, and identify lessons that can be learned to develop resilience in farming communities against future shocks. Methods We undertook a survey answered by 207 farmers across the UK, focusing on drivers of poor mental health and the effect of the COVID-19 pandemic. We also conducted 22 in-depth interviews with individuals in England, Scotland and Wales who provide mental health support to farmers. These explored how and why the COVID-19 pandemic affected the mental health of farmers. These interviews were supplemented by 93 survey responses from a similar group of support providers (UK-wide). Results We found that the pandemic exacerbated underlying drivers of poor mental health and wellbeing in farming communities. 67% of farmers surveyed reported feeling more stressed, 63% felt more anxious, 38% felt more depressed, and 12% felt more suicidal. The primary drivers of poor mental health identified by farmers during the pandemic were decreased social contact, issues with the general public on private land, and moving online for social events. Support providers also highlighted relationship and financial issues, illness, and government inspections as drivers of poor mental health. Some farmers, conversely, outlined positive impacts of the pandemic. Conclusion The COVID-19 pandemic is just one of many potential stressors associated with poor farming mental health and its impacts are likely to be long lasting and delayed. Multiple stressors affecting farmers at the same time can create a tipping point. Therefore, there is a need for long-term support and ongoing evaluation of the drivers of poor mental health in farming families.

  • Closed Access
    Authors: 
    Zhi Su; Peng Liu; Tong Fang;
    Publisher: Elsevier BV

    Abstract We construct a pandemic-induced fear (PIF) index to measure fear of the COVID-19 pandemic using Internet search volumes of the Chinese local search engine and empirically investigate the impact of fear of the pandemic on Chinese stock market returns. A reduced-bias estimation approach for multivariate regression is employed to address the issue of small-sample bias. We find that the PIF index has a negative and significant impact on cumulative stock market returns. The impact of PIF is persistent, which can be explained by mispricing from investors' excessive pessimism. We further reveal that the PIF index directly predicts stock market returns through noise trading. Investors' Internet search behaviors enhance the fear of the pandemic, and pandemic-induced fear determines future stock market returns, rather than the number of cases and deaths caused by the COVID-19 pandemic.

  • Open Access
    Authors: 
    Radeef Chundakkadan; Elizabeth Nedumparambil;
    Publisher: Elsevier BV

    Abstract The aim of this paper is two-fold. First, we investigate the nexus between investor attention to COVID-19 and daily returns in 59 countries. We use Google Search Volume Index to account for investor attention. Our empirical findings suggest that the search volume of the pandemic is negatively associated with daily returns. The effect was strong in the week that the World Health Organization declared it as pandemic and among advanced countries. Second, we explore the relationship between search volume and market volatility. The findings suggest that COVID-19 sentiment generated excess volatility in the market. Our findings remain robust with alternative specifications.

  • Closed Access
    Authors: 
    Fei-Ying Kuo; Tzai-Hung Wen;
    Publisher: Elsevier BV