Youth Development Agents' Needs: Challenges for Extension Volunteer Management Competencies in Nigeria

This study examined the needs of youth development agents as it affects extension volunteer managers' competencies. Youth development agencies who had registered with Global Youth Actions Network (GYAN) in Nigeria were used as the population of the study. A total of twenty nine (29) managers of these agencies with agricultural extension based activities were selected using purposive sampling technique. Structured questionnaire was administered online to elicit relevant information from the respondents for the purpose of the study. The study revealed that, majority (70%) of the respondents were male with an average age of twenty six (26) years. Out of the seventeen (17) areas of competencies identified among these managers, motivating youth volunteers ranked first, having a mean value of 4.07. The hypothesis testing carried out using correlation showed a significant relationship between agent's frequency of using volunteer administration and importance of volunteers in management (P<0.01) giving 0.653 while a significant relationship of 0.390 (P< 0.05) was also observed between importance of volunteers in management and training among agencies managers. It was also observed that volunteer agents could benefit from educational opportunities, resource materials and other support services in each of the areas of competencies. Regular training was therefore recommended for youth development agents to enable them update, improve and learn new strategies in the application of their competencies for extension service delivery.Keywords: Youth, Development, Agents' needs, Volunteer management, Competencies

A Novel Rank Aggregation-Based Hybrid Multifilter Wrapper Feature Selection Method in Software Defect Prediction

The high dimensionality of software metric features has long been noted as a data quality problem that affects the performance of software defect prediction (SDP) models. This drawback makes it necessary to apply feature selection (FS) algorithm(s) in SDP processes. FS approaches can be categorized into three types, namely, filter FS (FFS), wrapper FS (WFS), and hybrid FS (HFS). HFS has been established as superior because it combines the strength of both FFS and WFS methods. However, selecting the most appropriate FFS (filter rank selection problem) for HFS is a challenge because the performance of FFS methods depends on the choice of datasets and classifiers. In addition, the local optima stagnation and high computational costs of WFS due to large search spaces are inherited by the HFS method. Therefore, as a solution, this study proposes a novel rank aggregation-based hybrid multifilter wrapper feature selection (RAHMFWFS) method for the selection of relevant and irredundant features from software defect datasets. The proposed RAHMFWFS is divided into two stepwise stages. The first stage involves a rank aggregation-based multifilter feature selection (RMFFS) method that addresses the filter rank selection problem by aggregating individual rank lists from multiple filter methods, using a novel rank aggregation method to generate a single, robust, and non-disjoint rank list. In the second stage, the aggregated ranked features are further preprocessed by an enhanced wrapper feature selection (EWFS) method based on a dynamic reranking strategy that is used to guide the feature subset selection process of the HFS method. This, in turn, reduces the number of evaluation cycles while amplifying or maintaining its prediction performance. The feasibility of the proposed RAHMFWFS was demonstrated on benchmarked software defect datasets with Naïve Bayes and Decision Tree classifiers, based on accuracy, the area under the curve (AUC), and F-measure values. The experimental results showed the effectiveness of RAHMFWFS in addressing filter rank selection and local optima stagnation problems in HFS, as well as the ability to select optimal features from SDP datasets while maintaining or enhancing the performance of SDP models. To conclude, the proposed RAHMFWFS achieved good performance by improving the prediction performances of SDP models across the selected datasets, compared to existing state-of-the-arts HFS methods

Rapid increases in obesity in Jamaica, compared to Nigeria and the United States

<p>Abstract</p> <p>Background</p> <p>Weight gain in adulthood is now common in many populations, ranging from modest gains in developing countries to a substantial percentage of body weight in some Western societies. To examine the rate of change across the spectrum of low to high-income countries we compared rates of weight change in samples drawn from three countries, Nigeria, Jamaica and the United States.</p> <p>Methods</p> <p>Population samples from Nigeria (n = 1,242), Jamaica (n = 1,409), and the US (n = 809) were selected during the period 1995–1999 in adults over the age of 19; participation rates in the original survey were 96%, 60%, and 60%, respectively. Weight in (kg) was measured on 3 different occasions, ending in 2005. Multi-level regression models were used to estimate weight change over time and pattern-mixture models were applied to assess the potential effect of missing data on estimates of the model parameters.</p> <p>Results</p> <p>The unadjusted weight gain rate (standard error) was 0.34(0.06), 1.26(0.12), 0.34(0.19) kg/year among men and 0.43(0.06), 1.28(0.10), 0.40(0.15) kg/year among women in Nigeria, Jamaica, US, respectively. Regression-adjusted weight change rates were significantly different across country, sex, and baseline BMI. Adjusted weight gain in Nigeria, Jamaica and US was 0.31(0.05), 1.37(.04), and 0.52(0.05) kg/year respectively. Women in Nigeria and the US had higher weight gains than men, with the converse observed among Jamaicans. The obese experienced weight loss across all three samples, whereas the normal weight (BMI < 25) had significant weight gains. Missing data patterns had an effect on the rates of weight change.</p> <p>Conclusion</p> <p>Weight change in sample cohorts from a middle-income country was greater than in cohorts from either of the low- or high-income countries. The steep trajectory of weight gain in Jamaica, relative to Nigeria and the US, is most likely attributable to the accelerating effects of the cultural and behavioral shifts which have come to bear on transitional societies.</p

Y Chromosome Lineages in Men of West African Descent

The early African experience in the Americas is marked by the transatlantic slave trade from ∼1619 to 1850 and the rise of the plantation system. The origins of enslaved Africans were largely dependent on European preferences as well as the availability of potential laborers within Africa. Rice production was a key industry of many colonial South Carolina low country plantations. Accordingly, rice plantations owners within South Carolina often requested enslaved Africans from the so-called “Grain Coast” of western Africa (Senegal to Sierra Leone). Studies on the African origins of the enslaved within other regions of the Americas have been limited. To address the issue of origins of people of African descent within the Americas and understand more about the genetic heterogeneity present within Africa and the African Diaspora, we typed Y chromosome specific markers in 1,319 men consisting of 508 west and central Africans (from 12 populations), 188 Caribbeans (from 2 islands), 532 African Americans (AAs from Washington, DC and Columbia, SC), and 91 European Americans. Principal component and admixture analyses provide support for significant Grain Coast ancestry among African American men in South Carolina. AA men from DC and the Caribbean showed a closer affinity to populations from the Bight of Biafra. Furthermore, 30–40% of the paternal lineages in African descent populations in the Americas are of European ancestry. Diverse west African ancestries and sex-biased gene flow from EAs has contributed greatly to the genetic heterogeneity of African populations throughout the Americas and has significant implications for gene mapping efforts in these populations

Genome-Wide Local Ancestry Approach Identifies Genes and Variants Associated with Chemotherapeutic Susceptibility in African Americans

Chemotherapeutic agents are used in the treatment of many cancers, yet variable resistance and toxicities among individuals limit successful outcomes. Several studies have indicated outcome differences associated with ancestry among patients with various cancer types. Using both traditional SNP-based and newly developed gene-based genome-wide approaches, we investigated the genetics of chemotherapeutic susceptibility in lymphoblastoid cell lines derived from 83 African Americans, a population for which there is a disparity in the number of genome-wide studies performed. To account for population structure in this admixed population, we incorporated local ancestry information into our association model. We tested over 2 million SNPs and identified 325, 176, 240, and 190 SNPs that were suggestively associated with cytarabine-, 5′-deoxyfluorouridine (5′-DFUR)-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10−4). Importantly, some of these variants are found only in populations of African descent. We also show that cisplatin-susceptibility SNPs are enriched for carboplatin-susceptibility SNPs. Using a gene-based genome-wide association approach, we identified 26, 11, 20, and 41 suggestive candidate genes for association with cytarabine-, 5′-DFUR-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10−3). Fourteen of these genes showed evidence of association with their respective chemotherapeutic phenotypes in the Yoruba from Ibadan, Nigeria (p<0.05), including TP53I11, COPS5 and GAS8, which are known to be involved in tumorigenesis. Although our results require further study, we have identified variants and genes associated with chemotherapeutic susceptibility in African Americans by using an approach that incorporates local ancestry information

Enhanced Statistical Tests for GWAS in Admixed Populations: Assessment using African Americans from CARe and a Breast Cancer Consortium

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Bifunctional hydrous RuO2 nanocluster electrocatalyst embedded in carbon matrix for efficient and durable operation of rechargeable zinc-air batteries

Ruthenium oxide (RuO2) is the best oxygen evolution reaction (OER) electrocatalyst. Herein, we demonstrated that RuO2 can be also efficiently used as an oxygen reduction reaction (ORR) electrocatalyst, thereby serving as a bifunctional material for rechargeable Zn-air batteries. We found two forms of RuO2 (i.e. hydrous and anhydrous, respectively h-RuO2 and ah-RuO2) to show different ORR and OER electrocatalytic characteristics. Thus, h-RuO2 required large ORR overpotentials, although it completed the ORR via a 4e process. In contrast, h-RuO2 triggered the OER at lower overpotentials at the expense of showing very unstable electrocatalytic activity. To capitalize on the advantages of h-RuO2 while improving its drawbacks, we designed a unique structure (RuO2@C) where h-RuO2 nanoparticles were embedded in a carbon matrix. A double hydrophilic block copolymer-templated ruthenium precursor was transformed into RuO2 nanoparticles upon formation of the carbon matrix via annealing. The carbon matrix allowed overcoming the limitations of h-RuO2 by improving its poor conductivity and protecting the catalyst from dissolution during OER. The bifunctional RuO2@C catalyst demonstrated a very low potential gap (triangle EOER-ORR=ca. 1.0V) at 20 mA cm(-2). The Zn|| RuO2@C cell showed an excellent stability (i.e. no overpotential was observed after more than 40 h)