Women’s Political Participation and Politics of Disempowerment in Abia State of Nigeria

The paper examines women's political participation in Abia State of Nigeria with a view to determining the factors that constrain women’s equal representation in the political system. Women's political involvement in Abia State has remained increasingly low in spite of decades of struggle to ensure gender equity and women’s empowerment. This paper in addition to other known factors, situates the problem on the present trend of designating specific portfolios to women, which was intended to provide the women the opportunity of being represented in the policy making positions and processes in the polity. This in the opinion of the paper undermines, if not completely diminishes women’s drive to vie or aspire for other contestable (and even appointable) positions which would advance gender equity. In other words boxing women into one position dooms their chances. It is the view of the paper that there is need for a paradigm shift from the hitherto empowerment agenda to providing level playing ground that would enthrone gender equity. This has become necessary in view of the fact that women participation in politics has a potential of driving more and reasonable resource into community and national development. This study relied on the Chronological Analytic Approach in analysis and adopted the theory of representation as its theoretical guide. Keywords: Women, Political participation, Politics of disempowerment, Abia State

Parallel Batch-Dynamic Graph Connectivity

In this paper, we study batch parallel algorithms for the dynamic connectivity problem, a fundamental problem that has received considerable attention in the sequential setting. The most well known sequential algorithm for dynamic connectivity is the elegant level-set algorithm of Holm, de Lichtenberg and Thorup (HDT), which achieves $O(\log^2 n)$ amortized time per edge insertion or deletion, and $O(\log n / \log\log n)$ time per query. We design a parallel batch-dynamic connectivity algorithm that is work-efficient with respect to the HDT algorithm for small batch sizes, and is asymptotically faster when the average batch size is sufficiently large. Given a sequence of batched updates, where $\Delta$ is the average batch size of all deletions, our algorithm achieves $O(\log n \log(1 + n / \Delta))$ expected amortized work per edge insertion and deletion and $O(\log^3 n)$ depth w.h.p. Our algorithm answers a batch of $k$ connectivity queries in $O(k \log(1 + n/k))$ expected work and $O(\log n)$ depth w.h.p. To the best of our knowledge, our algorithm is the first parallel batch-dynamic algorithm for connectivity.Comment: This is the full version of the paper appearing in the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 201

Morbidity and mortality amongst infants of diabetic mothers admitted into a special care baby unit in Port Harcourt, Nigeria

<p>Abstract</p> <p>Background</p> <p>Infants born to diabetic women have certain distinctive characteristics, including large size and high morbidity risks. The neonatal mortality rate is over five times that of infants of non diabetic mothers and is higher at all gestational ages and birth weight for gestational age (GA) categories.</p> <p>The study aimed to determine morbidity and mortality pattern amongst infants of diabetic mothers (IDMS) admitted into the Special Care Baby Unit of University of Port Harcourt Teaching Hospital.</p> <p>Methods</p> <p>This was a study of prevalence of morbidity and mortality among IDMs carried out prospectively over a two year period. All IDMs (pregestational and gestational) admitted into the Unit within the period were recruited into the study.</p> <p>Data on delivery mode, GA, birth weight, other associated morbidities, investigation results, treatment, duration of hospital stay and outcome were collated and compared with those of infants of non diabetic mothers matched for GA and birth weight admitted within the same period. Maternal data were reviewed retrospectively. Data were analyzed using SPSS 16.0.</p> <p>Results</p> <p>Sixty percent of the IDMs were born to mothers with gestational diabetes, while 40% were born to mothers with pregestational DM. 38 (74.3%) were born by Caesarian section (CS), of which 20 (52.6%) were by emergency CS. There was no significant difference in emergency CS rates, when compared with controls, but non-IDMs were more likely to be delivered vaginally. The mean GA of IDMs was 37.84 weeks ± 1.88. 29 (61.7%) of them were macrosomic. The commonest morbidities were Hypoglycemia (significantly higher in IDMs than non-IDMs) and hyperbilirubinaemia in 30 (63.8%) and 26 (57.4%) respectively.</p> <p>There was no difference in morbidity pattern between infants of pre- gestational and gestational diabetic mothers. Mortality rate was not significantly higher in IDMs</p> <p>Conclusions</p> <p>The incidence of macrosomia in IDMs was high but high rates of emergency CS was not peculiar to them. Hypoglycaemia and hyperbilirubinaemia were the commonest morbidities in IDMs.</p> <p>Referring women with unstable metabolic control to specialized centers improves pre- and post- natal outcomes. Maternal-Infant centers for management of diabetes in pregnancy are advocated on a national scale to reduce associated morbidity and mortality</p

The Effect of Nucleotide Transfer from Some Microbes to Improve Plants for Biotechnological Advancement

The advance in plant biotechnology has some challenges with the evolutionary trend and methods adopted to resolve some of these problems: to improve the host morphological and genotypic features by nucleotide alteration leading to changes in mitochondrial molecular structure in the eukaryotic and prokaryotic plants. However, some biotechnological designs used in this research are DGGE, Phoretix 1D, and the Shannon-wiener index (H). While the microbial DNA concentration,&nbsp; virulent qualities coupled with the adaptative features of both the microbes and host plant and bioactive compounds reduction effects on the transformed host plant were the findings from this research

Ocean Governance and the Millennium Development Goals (MDGs): The Missing Links to Sustainable Development Goals (SDGs)

The oceans and seas are the source of life on earth and are therefore a crucial factor in determining global climate change, global economy and hence international relations.For these reasons, ocean governance must necessarily become part and parcel of the strategies for achieving the objectives sought in the Millennium Declaration of September 2000 and the new sustainable development project.This paper highlights the essence of the Law of the Sea and hence ocean governance and the role it could have played in achieving the objectives sought in Millennium Development Goals (MDGS) in Nigeria as well as the prospects for transiting to the current Sustainable Development Agenda (SDA).The paper thus equates ocean governance by means of the evolution of the law of the sea, which has progressively developed from two major principles to attend a climax with the 1982 Convention on the Law of the Sea otherwise known as UNCLOS III. The main thrust of the paper is that the opportunities provided by the law of the sea and hence ocean governance have provided impetus that can serve Nigeria as some of the most effective strategies for achieving SDGs having missed maximization in respect to the MDGs

Fast Evaluation of Interlace Polynomials on Graphs of Bounded Treewidth

We consider the multivariate interlace polynomial introduced by Courcelle (2008), which generalizes several interlace polynomials defined by Arratia, Bollobas, and Sorkin (2004) and by Aigner and van der Holst (2004). We present an algorithm to evaluate the multivariate interlace polynomial of a graph with n vertices given a tree decomposition of the graph of width k. The best previously known result (Courcelle 2008) employs a general logical framework and leads to an algorithm with running time f(k)*n, where f(k) is doubly exponential in k. Analyzing the GF(2)-rank of adjacency matrices in the context of tree decompositions, we give a faster and more direct algorithm. Our algorithm uses 2^{3k^2+O(k)}*n arithmetic operations and can be efficiently implemented in parallel.Comment: v4: Minor error in Lemma 5.5 fixed, Section 6.6 added, minor improvements. 44 pages, 14 figure

Rescue therapy for vasospasm following aneurysmal subarachnoid hemorrhage:a propensity score-matched analysis with machine learning

OBJECTIVE Rescue therapies have been recommended for patients with angiographic vasospasm (aVSP) and delayed cerebral ischemia (DCI) following subarachnoid hemorrhage (SAH). However, there is little evidence from randomized clinical trials that these therapies are safe and effective. The primary aim of this study was to apply game theory-based methods in explainable machine learning (ML) and propensity score matching to determine if rescue therapy was associated with better 3-month outcomes following post-SAH aVSP and DCI. The authors also sought to use these explainable ML methods to identify patient populations that were more likely to receive rescue therapy and factors associated with better outcomes after rescue therapy. METHODS Data for patients with aVSP or DCI after SAH were obtained from 8 clinical trials and 1 observational study in the Subarachnoid Hemorrhage International Trialists repository. Gradient boosting ML models were constructed for each patient to predict the probability of receiving rescue therapy and the 3-month Glasgow Outcome Scale (GOS) score. Favorable outcome was defined as a 3-month GOS score of 4 or 5. Shapley Additive Explanation (SNAP) values were calculated for each patient-derived model to quantify feature importance and interaction effects. Variables with high S HAP importance in predicting rescue therapy administration were used in a propensity score-matched analysis of rescue therapy and 3-month GOS scores. RESULTS The authors identified 1532 patients with aVSP or DCI. Predictive, explainable ML models revealed that aneurysm characteristics and neurological complications, but not admission neurological scores, carried the highest relative importance rankings in predicting whether rescue therapy was administered. Younger age and absence of cerebral ischemia/ infarction were invariably linked to better rescue outcomes, whereas the other important predictors of outcome varied by rescue type (interventional or noninterventional). In a propensity score-matched analysis guided by SHAP-based variable selection, rescue therapy was associated with higher odds of 3-month GOS scores of 4-5 (OR 1.63, 95% CI 1.22-2.17). CONCLUSIONS Rescue therapy may increase the odds of good outcome in patients with aVSP or DCI after SAH. Given the strong association between cerebral ischemia/infarction and poor outcome, trials focusing on preventative or therapeutic interventions in these patients may be most able to demonstrate improvements in clinical outcomes. Insights developed from these models may be helpful for improving patient selection and trial design

Development and validation of outcome prediction models for aneurysmal subarachnoid haemorrhage:the SAHIT multinational cohort study

Objective To develop and validate a set of practical prediction tools that reliably estimate the outcome of subarachnoid haemorrhage from ruptured intracranial aneurysms (SAH). Design Cohort study with logistic regression analysis to combine predictors and treatment modality. Setting Subarachnoid Haemorrhage International Trialists' (SAHIT) data repository, including randomised clinical trials, prospective observational studies, and hospital registries. Participants Researchers collaborated to pool datasets of prospective observational studies, hospital registries, and randomised clinical trials of SAH from multiple geographical regions to develop and validate clinical predicti