Farmers Perception and Adaptation to Climate Change: An Estimation of Willingness to Pay

This paper assesses farmers’ perception and adaptation to climate change to enhance policy towards tackling the challenges climate change poses to the farmers in Ghana. With regards to farmers’ perception and methods of adaptation, majority of the farmers perceived increase in temperature and decrease in rainfall pattern. Farmers’ level of adaptation was found to be relatively high with majority of the farmers using changing planting dates, different crop varieties, soil conservation and water harvesting as the major adaptation measures to climate change impacts. However, access to water, high cost of adaptation, lack of information, lack of knowledge on adaptation, insecure property rights, insufficient access to inputs and lack of credits were identified as the major barriers to adaptation. The probit regression estimation results indicated that the probability of willingness to pay for climate change mitigation policies increases with age, years of education and ownership of farm land.Perception, adaptation, climate change, willingnessto pay, probit regression, Agricultural and Food Policy, Farm Management, Production Economics, Productivity Analysis, GA, IN,

A THRESHOLD COINTEGRATION ANALYSIS OF ASYMMETRIC ADJUSTMENTS IN THE GHANAIAN MAIZE MARKETS

This paper analyzes the long-run equilibrium relationship between retail and wholesale Ghanaian maize prices with cointegration test assuming asymmetric adjustment. Using the Enders-Siklos asymmetric cointegration tests, it is found that the retail and wholesale prices are cointegrated with threshold adjustment. Furthermore, the adjustment process is asymmetric when the retail and wholesale prices adjust to achieve the long-term equilibrium. Finally, there is faster convergence for negative deviations from long-term equilibrium than for positive deviations. These results imply that price increases tend to persist whereas decreases tend to revert quickly towards equilibrium

A total variation-undecimated wavelet approach to chest radiograph image enhancement

Most often medical images such as X-Rays have a low dynamic range and many of their targeted features are difficult to identify. Intensity transformations that improve image quality usually rely onwavelet denoising and enhancement typically use the technique of thresholding to obtain better quality medical images. A disadvantage of wavelet thresholding is that even though it adequately removes noise in an image, it introduces unwanted artifacts into the image near discontinuities. We utilize a total variation method and an undecimated wavelet image enhancing algorithm for improving the image quality of chest radiographs. Our approach achieves a high level chest radiograph image deniosing in lung nodules detection while preserving the important features. Moreover, our method results in a high image sensitivity that reduces the average number of false positives on a test set of medical data

RANK-BASED ESTIMATION FOR COBB-DOUGLAS MODELLING IN THE PRESENCE OF OUTLIERS

Ordinary least square (OLS) has been widely used in estimating the Cobb-Douglas production function when analysing the empirical linkage between inputs and outputs. However, the estimates based on OLS technique may be biased by the presence of outliers. Rank-based regression estimation is resistant to outliers and may result in unbiased estimates. The objective of this study is therefore to investigate by use of Monte Carlo methods, the performance of the Rank-based regression and OLS methods in estimating the Cobb-Douglas regression model using data with and without outliers. Monte Carlo simulation results indicate that the estimates of the coefficients of the Cobb-Douglas regression model derived from the Least Squares and the Rank-based estimation methods are accurate and equivalent or close to their true values for normal data regardless of variability in sample size. For data with outliers, Least Squares method is affected by outliers and yields inaccurate estimates of the coefficients of the Cobb-Douglas model across various sample sizes. Rank-based estimation remains robust to outliers in large samples and provides estimates of the coefficients of the Cobb-Douglas Regression model that are accurate and nearly equivalent to their true values. The evidence from Monte Carlo experimentation suggests that the proposed Rank-based estimation is likely to do no worse than the OLS with normal dataset and promise to do better when the dataset has outliers within the Cobb-Douglas production function modelling context. The presence of outliers can bias the results of the OLS estimation of the Cobb-Douglas model and it is recommended that the use of Rank-based regression can be an appropriate method to avoid such biased estimates

The proliferation of motor tricycle usage in precarious transportation contexts and the performance of micro and small manufacturers

Micro and small businesses (MSBs) in developing countries increasingly use motor tricycles to navigate transportation-induced supply chain disruptions. However, there is a lack of empirical understanding of whether and when these resources benefit such firms. This study draws on the contingent resource-based theory to examine how motor tricycle deployment relates to the performance of MSBs under varying conditions of supply chain dynamism in a developing country. The study tests its hypotheses on primary data from 267 micro and small manufacturers in Ghana using moderated regression analysis. The results indicate that motor tricycle deployment positively relates to MSB performance in Ghana (β = 0.024, SE = 0.007, p = 0.001). The results further show that supply chain dynamism positively moderates the relationship between motor tricycle deployment and MSB performance (β = 0.008, SE = 0.004, p = 0.035). In contributing to the limited literature on the firm-level performance implications of the increasing use of motor tricycles among micro and small businesses in developing countries, this study's results underscore the importance of adopting a contingency-based approach to understand the complexities inherent in the relationship between motor tricycle deployment and firm performance in these settings

Elevated Circulating Angiogenic Progenitors and White Blood Cells Are Associated with Hypoxia-Inducible Angiogenic Growth Factors in Children with Sickle Cell Disease

We studied the number and function of angiogenic progenitor cells and growth factors in children aged 5–18 years without acute illness, 43 with Hemoglobin SS and 68 with normal hemoglobin. Hemoglobin SS subjects had at least twice as many mononuclear cell colonies and more circulating progenitor cell than Control subjects. Plasma concentrations of erythropoietin, angiopoietin-2, and stromal-derived growth factor (SDF)-1α were significantly higher in children with Hemoglobin SS compared to Control subjects. In a multivariate analysis model, SDF-1α concentration was found to be associated with both CPC number and total white blood cell count in the Hemoglobin SS group, suggesting that SDF-1α produced by ischemic tissues plays a role in mobilizing these cells in children with Hemoglobin SS. Despite having a higher number of angiogenic progenitor cells, children with Hemoglobin SS had slower migration of cultured mononuclear cells

Deploying aptameric sensing technology for rapid pandemic monitoring

The genome of virulent strains may possess the ability to mutate by means of antigenic shift and/or antigenic drift as well as being resistant to antibiotics with time. The outbreak and spread of these virulent diseases including avian influenza (H1N1), severe acute respiratory syndrome (SARS-Corona virus), cholera (Vibrio cholera), tuberculosis (Mycobacterium tuberculosis), Ebola hemorrhagic fever (Ebola Virus) and AIDS (HIV-1) necessitate urgent attention to develop diagnostic protocols and assays for rapid detection and screening. Rapid and accurate detection of first cases with certainty will contribute significantly in preventing disease transmission and escalation to pandemic levels. As a result, there is a need to develop technologies that can meet the heavy demand of an all-embedded, inexpensive, specific and fast biosensing for the detection and screening of pathogens in active or latent forms to offer quick diagnosis and early treatments in order to avoid disease aggravation and unnecessary late treatment costs. Nucleic acid aptamers are short, single-stranded RNA or DNA sequences that can selectively bind to specific cellular and biomolecular targets. Aptamers, as new-age bioaffinity probes, have the necessary biophysical characteristics for improved pathogen detection. This article seeks to review global pandemic situations in relation to advances in pathogen detection systems. It particularly discusses aptameric biosensing and establishes application opportunities for effective pandemic monitoring. Insights into the application of continuous polymeric supports as the synthetic base for aptamer coupling to provide the needed convective mass transport for rapid screening is also presented

Assessment of Water Quality and Heavy Metal Levels in Water and Bottom Sediment Samples from Mokwé Lagoon, Accra, Ghana

Abstract: The current study deals with the physicochemical characteristics of water samples from the Mokwé Lagoon in addition to trace heavy metals (Cd, Cr, Ni, Pb and Zn) in the lagoon water and bottom sediments. The results indicated relatively high ionic content which was reflected in high conductivity, total dissolved Solids, alkalinity, hardness and chloride levels; and low nutrient content. The trace heavy metal levels in the lagoon water were found within good range of international guideline limits for natural waters. In contrast, the metallic levels in the sediment were high. The levels of metal contamination and distribution in the sediment samples were assessed using geoaccumulation index, enrichment factor, contamination factor and pollution load factor. The metal index analysis indicated high enrichment of the metals (especially Cr and Ni) which reflected anthropogenic effects of contamination attributable to several sources. The study calls for constant environmental monitoring to forestall any heavy metal hazard which could be detrimental to the aquatic ecosystem of the lagoon

ALCAM Regulates Motility, Invasiveness, and Adherens Junction Formation in Uveal Melanoma Cells

ALCAM, a member of the immunoglobulin superfamily, has been implicated in numerous developmental events and has been repeatedly identified as a marker for cancer metastasis. Previous studies addressing ALCAM’s role in cancer have, however, yielded conflicting results. Depending on the tumor cell type, ALCAM expression has been reported to be both positively and negatively correlated with cancer progression and metastasis in the literature. To better understand how ALCAM might regulate cancer cell behavior, we utilized a panel of defined uveal melanoma cell lines with high or low ALCAM levels, and directly tested the effects of manipulating these levels on cell motility, invasiveness, and adhesion using multiple assays. ALCAM expression was stably silenced by shRNA knockdown in a high-ALCAM cell line (MUM-2B); the resulting cells displayed reduced motility in gap-closure assays and a reduction in invasiveness as measured by a transwell migration assay. Immunostaining revealed that the silenced cells were defective in the formation of adherens junctions, at which ALCAM colocalizes with N-cadherin and ß-catenin in native cells. Additionally, we stably overexpressed ALCAM in a low-ALCAM cell line (MUM-2C); intriguingly, these cells did not exhibit any increase in motility or invasiveness, indicating that ALCAM is necessary but not sufficient to promote metastasis-associated cell behaviors. In these ALCAM-overexpressing cells, however, recruitment of ß-catenin and N-cadherin to adherens junctions was enhanced. These data confirm a previously suggested role for ALCAM in the regulation of adherens junctions, and also suggest a mechanism by which ALCAM might differentially enhance or decrease invasiveness, depending on the type of cadherin adhesion complexes present in tissues surrounding the primary tumor, and on the cadherin status of the tumor cells themselves

Activated leukocyte cell adhesion molecule in breast cancer: prognostic indicator

INTRODUCTION: Activated leukocyte cell adhesion molecule (ALCAM) (CD166) is an immunoglobulin molecule that has been implicated in cell migration. The present study examined the expression of ALCAM in human breast cancer and assessed its prognostic value. METHODS: The immunohistochemical distribution and location of ALCAM was assessed in normal breast tissue and carcinoma. The levels of ALCAM transcripts in frozen tissue (normal breast, n = 32; breast cancer, n = 120) were determined using real-time quantitative PCR. The results were then analyzed in relation to clinical data including the tumor type, the grade, the nodal involvement, distant metastases, the tumor, node, metastasis (TNM) stage, the Nottingham Prognostic Index (NPI), and survival over a 6-year follow-up period. RESULTS: Immunohistochemical staining on tissue sections in ducts/acini in normal breast and in breast carcinoma was ALCAM-positive. Differences in the number of ALCAM transcripts were found in different types of breast cancer. The level of ALCAM transcripts was lower (P = 0.05) in tumors from patients who had metastases to regional lymph nodes compared with those patients without, in higher grade tumors compared with Grade 1 tumors (P < 0.01), and in TNM Stage 3 tumors compared with TNM Stage 1 tumors (P < 0.01). Tumors from patients with poor prognosis (with NPI > 5.4) had significantly lower levels (P = 0.014) of ALCAM transcripts compared with patients with good prognosis (with NPI < 3.4), and tumors from patients with local recurrence had significantly lower levels than those patients without local recurrence or metastases (P = 0.04). Notably, tumors from patients who died of breast cancer had significantly lower levels of ALCAM transcripts (P = 0.0041) than those with primary tumors but no metastatic disease or local recurrence. Patients with low levels of ALCAM transcripts had significantly (P = 0.009) more incidents (metastasis, recurrence, death) compared with patients with primary breast tumors with high levels of ALCAM transcripts. CONCLUSIONS: In the present panel of breast cancer specimens, decreased levels of ALCAM correlated with the nodal involvement, the grade, the TNM stage, the NPI, and the clinical outcome (local recurrence and death). The data suggest that decreased ALCAM expression is of clinical significance in breast cancer, and that reduced expression indicates a more aggressive phenotype and poor prognosis