Social networks, rice value chain participation and market performance of smallholder farmers in Ghana

This paper examines the impact of rice value chain participation and social networks on smallholder farmers' market performance outcomes (paddy price, quantity of paddy traded, and net returns), using data from a recent survey of 458 smallholder rice farmers in northern Ghana. We employed a treatment effects model to account for potential selection bias associated with observable and unobservable factors. The empirical results reveal that smallholder farmers' participation in a rice value chain is associated with increased paddy price, quantity traded, and net returns. We also find that value chain participation decisions and market performance are positively and significantly influenced by social networks. The empirical results also suggest that sex, farm size, mobile phone ownership, and access to credit significantly increase paddy prices, quantity traded, and net returns of smallholder rice farmers in the value chain

Lyra's Cosmology of Massive String in Anisotropic Bianchi-II Space-time

The paper deals with a spatially homogeneous and totally anisotropic Bianchi II cosmological models representing massive strings in normal gauge for Lyra's manifold. The modified Einstein's field equations have been solved by applying variation law for Hubble's parameter. This law generates two type of solutions for average scale factor, one is of power law type and other is of exponential law type. The power law describes the dynamics of Universe from big bang to present epoch while exponential law seems reasonable to project dynamics of future Universe. It has been found that the displacement actor $(\beta)$ is a decreasing function of time and it approaches to small positive value at late time, which is collaborated with Halford (1970) as well as recent observations of SN Ia. The study reveals that massive strings dominate in early Universe and eventually disappear from Universe for sufficiently large time, which is in agreement with the current astronomical observations.Comment: 12 pages, 5 figure

Allelopathic potential in rice - a biochemical tool for plant defence against weeds

Rice is a key crop for meeting the global food demand and ensuring food security. However, the crop has been facing great problems to combat the weed problem. Synthetic herbicides pose a severe threat to the long-term viability of agricultural output, agroecosystems, and human health. Allelochemicals, secondary metabolites of allelopathic plants, are a powerful tool for biological and eco-friendly weed management. The dynamics of weed species in various situations are determined by crop allelopathy. Phenolics and momilactones are the most common allelochemicals responsible for herbicidal effects in rice. The dispersion of allelochemicals is influenced not only by crop variety but also by climatic conditions. The most volatile chemicals, such as terpenoids, are usually emitted by crop plants in drought-stricken areas whereas the plants in humid zones release phytotoxins that are hydrophilic in nature, including phenolics, flavonoids, and alkaloids. The allelochemicals can disrupt the biochemical and physiological processes in weeds causing them to die finally. This study insight into the concepts of allelopathy and allelochemicals, types of allelochemicals, techniques of investigating allelopathic potential in rice, modes of action of allelochemicals, pathways of allelochemical production in plants, biosynthesis of allelochemicals in rice, factors influencing the production of allelochemicals in plants, genetical manipulation through breeding to develop allelopathic traits in rice, the significance of rice allelopathy in sustainable agriculture, etc. Understanding these biological phenomena may thus aid in the development of new and novel weed-control tactics while allowing farmers to manage weeds in an environmentally friendly manner

Differential modulation of immune response and cytokine profiles in the bursae and spleen of chickens infected with very virulent infectious bursal disease virus

Background: Very virulent infectious bursal disease virus (vvIBDV) induces immunosuppression and inflammation in young birds, which subsequently leads to high mortality. In addition, infectious bursal disease (IBD) is one of the leading causes of vaccine failure on farms. Therefore, understanding the immunopathogenesis of IBDV in both the spleen and the bursae could help effective vaccine development. However, previous studies only profiled the differential expression of a limited number of cytokines, in either the spleen or the bursae of Fabricius of IBDV-infected chickens. Thus, this study aims to evaluate the in vitro and in vivo immunoregulatory effects of vvIBDV infection on macrophage-like cells, spleen and bursae of Fabricius. Results: The viral load was increased during the progression of the in vitro infection in the HD11 macrophage cell line and in vivo, but no significant difference was observed between the spleen and the bursae tissue. vvIBDV infection induced the expression of pro-inflammatory and Th1 cytokines, and chemokines from HD11 cells in a time- and dosage-dependent manner. Furthermore, alterations in the lymphocyte populations, cytokine and chemokine expression, were observed in the vvIBDV-infected spleens and bursae. A drastic rise was detected in numbers of macrophages and pro-inflammatory cytokine expression in the spleen, as early as 2 days post-infection (dpi). On 4 dpi, macrophage and T lymphocyte infiltration, associated with the peak expression of pro-inflammatory cytokines in the bursae tissues of infected chickens were observed. The majority of the significantly regulated pro-inflammatory cytokines and chemokines, in vvIBDV-infected spleens and bursae, were also detected in vvIBDV-infected HD11 cells. This cellular infiltration subsequently resulted in a sharp rise in nitric oxide (NO) and lipid peroxidation levels. Conclusion: This study suggests that macrophage may play an important role in regulating the early expression of pro-inflammatory cytokines, first in the spleen and then in the bursae, the latter tissue undergoing macrophage infiltration at 4 dpi

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Using Constructivist Approach to Enhance Students Understanding of Logarithmic Functions: A Case Study of Kalpohin Senior High School, Tamale-Ghana

This paper deals with using constructivist approach to enhance studentsrsquo understanding of logarithmic function in Kalpohin Senior High School. Purposive sampling technique was employed to obtain a sample (n = 60) of male and female second year Agricultural Science and Home Economics students from Kalpohin Senior High School in Tamale, the Northern Region of Ghana. A constructivist-based instructional (CBI) approach was employed and evaluated using three instruments- pre-test, post-test and unstructured interviews to measure studentsrsquo understanding of logarithmic function, their attitudes and views about Constructivist approach

Pengaruh pendidikan dan pelatihan terhadap kinerja guru SMP Negeri 1 Kota Makassar

vii, 92 ha

Dual continuum fluid flow simulation in stress sensitive naturally fractured reservoirs

Fluid flow simulation for naturally fractured reservoirs is a significant and challenging task. A large part of the world's remaining hydrocarbon reserves are contained within such reservoirs. Recent advancement in fracture characterization techniques could result in very comprehensive discrete fracture network models. However, the models' arbitrary fracture size, orientation and spatial distribution create complex flow paths and heavy computational workload for a simulation program. The complexity is further raised, taking into account the effect of field stresses on the deformable fractures and rock. Previous reservoir simulation works did not incorporate these multiple facies of a detailed geological modeling in their production forecast. In the present work, a fracture network has been generated from author's previous work, combining statistical and spatial analyses, object-based modelling and conditional global optimization. For purpose of fluid flow simulation, Fractures are treated as discrete objects based on their length and each fracture is modeled implicitly and upscaled using grid based permeability tensor concept. A dual continuum fluid flow simulation model is developed and validated, which is able to handle fluid flow between matrix-fracture, matrix-matrix, and fracture- fracture and effects of deformation. In this work, the geomechanics solution is decomposed into matrix and fracture parts and used to compute their dynamic porosity and permeability separately. The model is validated against analytical data and data published in literature. The results show that the model can overcome problems existing in previous models in relation to computational resources, flow interactions between matrix and fracture and effect of deformation on fluid flow. The examples show that deformation has a major impact on productivity or injectivity, and the need of integrated fracture modelling for more accurate production forecasting