The entrepreneurship potential of rural areas: soap production as a side business for Tanzanian rice farmers

Purpose: This study examines soap production’s entrepreneurship potential and profitability as a supplementary business for rural rice farmers in Tanzania to promote their economic independence.Design/ Methodology/ Approach: We randomly sampled and interviewed about ten smallscale soap manufacturers in urban Tanzania gathered from 2019-2021 to develop a soap production business strategy for rural farmers at a similar scale. Considering the Voronoi theory, we calculated the distance from the rural areas to urban centres to determine the transportation costs, which particularly burden rural farmers. Soap production costs and profitability were determined based on transportation costs and raw material prices.Findings: Rural farmers would incur high transportation costs, given the high average distance to the nearest urban centre (sometimes > 100 km). Nevertheless, producing their rice bran oil, valuable raw material for soap production, would give them a competitive advantage over urban producers.Research Limitation: The study’s proposed strategy can be applied to similar contexts to reduce the urban-rural entrepreneurship divide.Practical Implication: Soaps made using rice bran oil help farmers reuse agricultural waste. Their active ingredients also increase their marketability as high-end cosmetic products, providing farmers with additional income.Social Implication: Commercializing agricultural residues such as rice bran increases farmers’ revenues and reduces CO2 emissions by preventing the residues’ incineration; this creates a virtuous cycle in society.Originality/ Value: This study presents a more realistic business strategy for rural Tanzanian farmers, as, unlike previous studies, it considers not only direct costs but also transportation costs

Predictors of COVID-19 epidemics in countries of the World Health Organization African Region

Countries of the World Health Organization (WHO) African Region have experienced a wide range of coronavirus disease 2019 (COVID-19) epidemics. This study aimed to identify predictors of the timing of the first COVID-19 case and the per capita mortality in WHO African Region countries during the first and second pandemic waves and to test for associations with the preparedness of health systems and government pandemic responses. Using a region-wide, country-based observational study, we found that the first case was detected earlier in countries with more urban populations, higher international connectivity and greater COVID-19 test capacity but later in island nations. Predictors of a high first wave per capita mortality rate included a more urban population, higher pre-pandemic international connectivity and a higher prevalence of HIV. Countries rated as better prepared and having more resilient health systems were worst affected by the disease, the imposition of restrictions or both, making any benefit of more stringent countermeasures difficult to detect. Predictors for the second wave were similar to the first. Second wave per capita mortality could be predicted from that of the first wave. The COVID-19 pandemic highlights unanticipated vulnerabilities to infectious disease in Africa that should be taken into account in future pandemic preparedness planning

Adaptive antenna selection and Tx/Rx beamforming for large-scale MIMO systems in 60 GHz channels

We consider a large-scale MIMO system operating in the 60 GHz band employing beamforming for high-speed data transmission. We assume that the number of RF chains is smaller than the number of antennas, which motivates the use of antenna selection to exploit the beamforming gain afforded by the large-scale antenna array. However, the system constraint that at the receiver, only a linear combination of the receive antenna outputs is available, which together with the large dimension of the MIMO system makes it challenging to devise an efficient antenna selection algorithm. By exploiting the strong line-of-sight property of the 60 GHz channels, we propose an iterative antenna selection algorithm based on discrete stochastic approximation that can quickly lock onto a near-optimal antenna subset. Moreover, given a selected antenna subset, we propose an adaptive transmit and receive beamforming algorithm based on the stochastic gradient method that makes use of a low-rate feedback channel to inform the transmitter about the selected beams. Simulation results show that both the proposed antenna selection and the adaptive beamforming techniques exhibit fast convergence and near-optimal performance

Cell Walls of Saccharomyces cerevisiae Differentially Modulated Innate Immunity and Glucose Metabolism during Late Systemic Inflammation

BACKGROUND: Salmonella causes acute systemic inflammation by using its virulence factors to invade the intestinal epithelium. But, prolonged inflammation may provoke severe body catabolism and immunological diseases. Salmonella has become more life-threatening due to emergence of multiple-antibiotic resistant strains. Mannose-rich oligosaccharides (MOS) from cells walls of Saccharomyces cerevisiae have shown to bind mannose-specific lectin of Gram-negative bacteria including Salmonella, and prevent their adherence to intestinal epithelial cells. However, whether MOS may potentially mitigate systemic inflammation is not investigated yet. Moreover, molecular events underlying innate immune responses and metabolic activities during late inflammation, in presence or absence of MOS, are unknown. METHODS AND PRINCIPAL FINDINGS: Using a Salmonella LPS-induced systemic inflammation chicken model and microarray analysis, we investigated the effects of MOS and virginiamycin (VIRG, a sub-therapeutic antibiotic) on innate immunity and glucose metabolism during late inflammation. Here, we demonstrate that MOS and VIRG modulated innate immunity and metabolic genes differently. Innate immune responses were principally mediated by intestinal IL-3, but not TNF-α, IL-1 or IL-6, whereas glucose mobilization occurred through intestinal gluconeogenesis only. MOS inherently induced IL-3 expression in control hosts. Consequent to LPS challenge, IL-3 induction in VIRG hosts but not differentially expressed in MOS hosts revealed that MOS counteracted LPS's detrimental inflammatory effects. Metabolic pathways are built to elucidate the mechanisms by which VIRG host's higher energy requirements were met: including gene up-regulations for intestinal gluconeogenesis (PEPCK) and liver glycolysis (ENO2), and intriguingly liver fatty acid synthesis through ATP citrate synthase (CS) down-regulation and ATP citrate lyase (ACLY) and malic enzyme (ME) up-regulations. However, MOS host's lower energy demands were sufficiently met through TCA citrate-derived energy, as indicated by CS up-regulation. CONCLUSIONS: MOS terminated inflammation earlier than VIRG and reduced glucose mobilization, thus representing a novel biological strategy to alleviate Salmonella-induced systemic inflammation in human and animal hosts

A year of genomic surveillance reveals how the SARS-CoV-2 pandemic unfolded in Africa

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Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees