An Empirical Model for Thyroid Disease Classification using Evolutionary Multivariate Bayseian Prediction Method

Thyroid diseases are widespread worldwide. In India too, there is a significant problems caused due to thyroid diseases. Various research studies estimates that about 42 million people in India suffer from thyroid diseases [4]. There are a number of possible thyroid diseases and disorders, including thyroiditis and thyroid cancer. This paper focuses on the classification of two of the most common thyroid disorders are hyperthyroidism and hypothyroidism among the public. The National Institutes of Health (NIH) states that about 1% of Americans suffer from Hyperthyroidism and about 5% suffer from Hypothyroidism. From the global perspective also the classification of thyroid plays a significant role. The conditions for the diagnosis of the disease are closely linked, they have several important differences that affect diagnosis and treatment. The data for this research work is collected from the UCI repository which undergoes preprocessing. The preprocessed data is multivariate in nature. Curse of Dimensionality is followed so that the available 21 attributes is optimized to 10 attributes using Hybrid Differential Evolution Kernel Based Navie Based algorithm. The subset of data is now supplied to Kernel Based NaEF;ve Bayes classifier algorithm in order to check for the fitness

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

Formaldehyde–free sticklac and arhar stick composite board

314-318Sticklac has been used as a binding material to prepare formaldehyde-free composite board from arhar (Cajanus cajan) stick agro waste. Effects of sticklac obtained from kusmi and rangeeni strain, binder content, press-cycle, particle type, moisture content, density of board and wax emulsion as additive are studied on physical and mechanical properties of board. Tests of modulus of rupture, tensile strength perpendicular to surface of board, screw withdrawal force, water absorption and thickness swelling have indicated that composite board prepared using sticklac in alcoholic solution can meet required standard for interior grade with regard to above properties

Factors Associated With the Recurring Cholera Outbreaks in Sinazongwe District of Southern Zambia

Objective: Possible risk factors associated with the recurring Cholera outbreaks in Malima and Nkandabbwe communities as well as know the available knowledge in managing and preventing the disease.Methods: The data was derived from mixed methods of descriptive and analytical cross sectional design with both quantitative and qualitative data collection strategies employed. Analyses of potential risk factors were stratified by safe drinking water, safe waste disposal, knowledge levels and climatic variations. Data was presented in frequency tables. Chi square tests were done to determine possible associations. All variables that were significant multiple logistic regression analysis was performed to control for confounders.Results: There was a statistical significance in terms of households hand washing with safe water as well as saving hot food [X² = 19.3783, df=4, P value = 0.001]. A range of variables from number of people in a household, occupation, main source of water, water treatment, reasons not treating water to knowledge about cholera were all found significant when X² tests were performed. However, after running the multivariate regression analysis test, only number of people in a household [coef =.0712297; Std.Err = .0263932; t=2.70; p=0.008; 95CI .0190736 - .1233858] and the main source of drinking water were statistically significant [ coef = -.0566683; Std.Err = .011744; t=-4.83; p=0.000; 95CI -.0798758 - -.0334607]. The rainfall patterns produced a correlation of 0.40000 was significant at p value 0.05. Though small, the correlation is significant and suggests that cholera cases vary with rainfall patterns for each year. Increased rainfall patterns may be associated with high numbers of reported cases.Conclusion: Water treatment was found to be occasional and most household's access water from surface sources such as rivers, lakes and streams. Chlorine is well known for water purification but social marketing is lacking due to free distributions