Bundles and Hotspots of Multiple Ecosystem Services for Optimized Land Management in Kentucky, United States

Ecosystem services are benefits that the natural environment provides to support human well-being. A thorough understanding and assessment of these services are critical to maintain ecosystem services flow through sustainable land management to optimize bundles of ecosystem services provision. Maximizing one particular ecosystem service may lead to reduction in another. Therefore, identifying ecosystem services tradeoffs and synergies is key in addressing this challenge. However, the identification of multiple ecosystem services tradeoffs and synergies is still limited. A previous study failed to effectively capture the spatial interaction among ecosystem services as it was limited by “space-to-time” substitution method used because of temporal data scarcity. The study was also limited by using land use types in creating ecosystem services, which could lead to some deviations. The broad objective of this study is therefore to examine the bundles and hotspots of multiple ecosystem services and their tradeoffs in Kentucky, U.S. The study combined geographic data and spatially-explicit models to identify multiple ecosystem services bundles and hotspots, and determined the spatial locations of ecosystem services hotspots. Results showed that the spatial interactions among ecosystem services were very high: of the 21 possible pairs of ecosystem services, 17 pairs were significantly correlated. The seven ecosystem services examined can be bundled into three groups, geographically clustered on the landscape. These results support the hypothesis that some groups of ecosystem services provision can present similar spatial patterns at a large mesoscale. Understanding the spatial interactions and bundles of the ecosystem services provides essential information for evidence-based sustainable land management

Towards Adequate Policy Enhancement: An AI-Driven Decision Tree Model for Efficient Recognition and Classification of EPA Status via Multi-Emission Parameters

Accurate and timely evaluation and assessment of emission data and its impact on environmental status has been a key challenge due to the conventional manual approach utilized for independently computing most emission parameters. To resolve this long-standing issue, we proposed an Artificial Intelligence (AI)-driven Decision Tree model to adequately classify Environmental Protection Agency (EPA) status based on multiple Emission Parameters. The model's performance was systematically evaluated using multiple emission parameters obtained from a two-stroke motorcycle dataset collected in Nigeria across various metrics such as K-S Statistics, Confusion Matrix, Correlation Heat Map, Decision Tree, Validation Curve, and Threshold Plot. The K-S Statistics plot's experimental results showed a considerable correlation between HC, CO, and the target variable, with values ranging from 0.75-0.80. At the same time, CO2 and O2 do not correlate with the target variable with values between 0.00 and 0.09. The Confusion Matrix revealed that the proposed model has an overall accuracy of 99.9% with 481 true positive predictions and 75 true negative predictions, indicating the effectiveness of the proposed AI-driven model. In conclusion, our proposed AI-driven model can effectively classify EPA status based on multiple emission parameters with high accuracy, which may spur positive advancement in policy enhancement for proper environmental management

Potential Economic Impacts of Allocating More Land for Bioenergy Biomass Production in Virginia

The growing attention to renewable energy and rural development has created greater demand for production of biomass feedstock for bioenergy. However, forest growth rates and the amount of land in most existing forests may not be sufficient to sustainably supply the forest biomass required to support existing forest products industries and the expanding bioenergy industry. Additionally, concerns about agricultural land use competition have dampened expansion of biomass production on agricultural land base. One of the ways to meet the growing forest biomass feedstock demand for bioenergy production is by allocating currently marginal non-forested land for growing bioenergy feedstocks. In Virginia, about 80% of forestland is under nonindustrial private forest ownership. The land use allocation decisions of these private owners are critical for the supply of the forest biomass feedstock to support bioenergy production. We apply a computable general equilibrium model to assess the economy-wide impacts of forestland owners’ willingness to plant pine on non-forested land for woody bioenergy in Virginia. We consider three counterfactual scenarios of biomass feedstock supply increase as intermediate demand for bioenergy production based on forestland owners’ willingness to accept biomass bid prices to set aside more non-forested land for biomass production in Virginia under general equilibrium conditions. Overall, the results show an increase in social welfare and household utility but a marginal decline in GDP. However, increased demand of biomass from logging sector depressed the manufacturing sector (the wood manufacturing sub-sector particularly), which also relies on the logging sector for its intermediate inputs. Results from this study provide insights into the bioenergy land use competition debate, and pathways towards sustainable bioenergy feedstock supply

African families and AIDS : context, reactions and potential interventions

This paper reviews publications and research reports on how sub-Saharan African families have been affected by, and reacted to, the AIDS epidemic. The nature of the African family and its variation across the regions is shown to be basic to both an understanding of how the epidemic spread and of its impact. The volume of good social science research undertaken until now on the disease in Africa is shown to be extremely small relative to the need

African families and AIDS : context, reactions and potential interventions

This paper reviews publications and research reports on how sub-Saharan African families have been affected by, and reacted to, the AIDS epidemic. The nature of the African family and its variation across the regions is shown to be basic to both an understanding of how the epidemic spread and of its impact. The volume of good social science research undertaken until now on the disease in Africa is shown to be extremely small relative to the need

Optimal Television Adverts Selection, Case Study: Ghana Television (GTV)

Abstract: The Knapsack Problems are among the simplest integer programs, which are NP-hard. Problems in this class are typically concerned with selecting from a set of given items, each with a specified weight and value, a subset of items whose weight sum does not exceed a prescribed capacity and whose value is maximum. The specific problem that arises depends on the number of knapsacks (single or multiple) to be filled and on the number of available items of each type (bounded or unbounded). In this research paper, we shall consider the application of classical 0-1 knapsack problem with a single constraint to selection of television advertisements at critical periods such as prime time news, news adjacencies, Break in News and peak times using the simple heuristic algorithm

Constraints Associated with the Marketing Channel of Lettuce and Cabbage Trade in Ghana

The present study aims to identify inefficiencies or bottlenecks in the marketing channel for lettuce and cabbage trade in Ghana which may be lowering economic incentives for producers and traders. It also aims to assess better ways in which local communities could benefit from lettuce and cabbage trade for poverty alleviation and livelihood improvement. The study focuses on the following central research questions: What constraints are associated with the marketing channel of lettuce and cabbage trade in Ghana which may be lowering economic incentives for producers and traders?  What are the ways in which local communities can better benefit from lettuce and cabbage trade for poverty alleviation and livelihood improvement? This study covers gaps in the existing marketing channels of lettuce and cabbage trade; proposes how the associated constraints could be solved to better protect the chain, and explores the application of the findings in other contexts. It presupposes a thorough understanding of the social, cultural, ecological and economic factors shaping lettuce and cabbage production in Ghana

Artificial and Natural Radioactivity Measurements and Radiation Dose Assessment in the Vicinity of Ghana Nuclear Research Reactor-1 (GHARR-1)

Radioactivity concentrations of <sup>226</sup>Ra, <sup>232</sup>Th, <sup>40</sup>K and <sup>137</sup>Cs in soil samples and water sources around the Ghana Research Reactor-1 (GHARR-1) and the immediate surroundings have been measured using gamma spectrometry. The primary aim of the study was to establish baseline radioactivity levels in the environs of GHARR-1. The average activity concentration of <sup>226</sup>Ra, <sup>232</sup>Th, <sup>40</sup>K and <sup>137</sup>Cs were 22.3 ± 1.12 Bq kg<sup>-1</sup>, 49.8 ± 1.60Bq kg-1, 99.60 ± 5.81 Bq kg<sup>-1</sup> and 1.48 ± 0.25 Bq kg<sup>-1</sup> for soil and 0.60 ± 0.11 Bq l<sup>-1</sup>, 2.13 ± 0.21 Bq l<sup>-1</sup>, 10.75 ± 0.84 Bq l<sup>-1</sup> and 0.47 ± 0.05 Bq l<sup>-1</sup>for the water, respectively. The <sup>226</sup>Ra and <sup>232</sup>Th concentrations compare quite well with world averages, whilst the <sup>40</sup>K concentration was lower than the world average. The levels of <sup>137</sup>Cs observed in the samples are within the range of ‘background’  concentrations. The estimated average annual effective doses from external exposure to soil and ingestion of water samples were calculated to be 0.06 mSv and 0.53 mSv, respectively. The estimated outdoor  external gamma dose rate measured in air ranged from 20-430 nGy h<sup>-1</sup> with an average value of 100 nGy h<sup>-1</sup>, which is higher than the world average value of 59 nGy h<sup>-1</sup>. In the case of water samples, the average value was higher than the guidance level of 0.1 mSv y<sup>-1</sup>, as recommended by the European Union and the World Health Organization