Emergence and spread of two SARS-CoV-2 variants of interest in Nigeria.

Identifying the dissemination patterns and impacts of a virus of economic or health importance during a pandemic is crucial, as it informs the public on policies for containment in order to reduce the spread of the virus. In this study, we integrated genomic and travel data to investigate the emergence and spread of the SARS-CoV-2 B.1.1.318 and B.1.525 (Eta) variants of interest in Nigeria and the wider Africa region. By integrating travel data and phylogeographic reconstructions, we find that these two variants that arose during the second wave in Nigeria emerged from within Africa, with the B.1.525 from Nigeria, and then spread to other parts of the world. Data from this study show how regional connectivity of Nigeria drove the spread of these variants of interest to surrounding countries and those connected by air-traffic. Our findings demonstrate the power of genomic analysis when combined with mobility and epidemiological data to identify the drivers of transmission, as bidirectional transmission within and between African nations are grossly underestimated as seen in our import risk index estimates

Pro forma

Network coding treats data as mathematical objects which can be transformed at network nodes in contrast to the traditional multi-commodity fluid model for network information flow where data can only be replicated or routed. Most previous work in this area has been largely theoretical and simulation-based. The original aim of this project is thus to select and develop an encoder/decoder pair suitable for deploying the concept of network coding in practical systems such as a large-scale content distribution application. If time permitted, we further aimed at demonstrating how the encoder/decoder pair can be integrated into the application. Work Completed A family of encoder/decoder with suitable encoding/decoding time and memory requirement was selected, implemented in C/C++ and tested. These good codes are based on sparse matrices and iterative decoding. The content distribution network was simulated as a Packet Erasure Channel. We setup a private content distribution network of cTorrent clients and BNBT Trinity Edition tracker, devised a scheme for integrating the encoder/decoder into the cTorrent network for network coding, outlined the changes that need be made to cTorrent source code and described how they can be implemented

Implementation of Quasi-Newton Method Based on BFGS Algorithm for Identification and Optimization of Signal Propagation Loss Model Parameters

Abstract—Reliable and precise predictive modelling of signal losses along the communications paths and channels of propagated radio frequency waves is fundamental to the proper design, modelling, operation, and management of mobile broadband cellular networks. As such, the identification and tuning-based estimation of the signal propagation loss parameters has advanced into a recurrent task in the field of radio frequency and telecommunication engineering. Amongst the critical challenges known with identification and predictive estimation signal propagation loss parameters, the generic model-empirical data tuning approach is very vital, yet a most often disregarded and tough optimization problem. Here, a robust and fast computation capacity of Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm Quasi-Newton (QN) method based on the BFGS algorithm is presented for precise identification and optimization of generic log-distance propagation loss model parameters. The proposed QN based BFGS algorithm has been implemented for prognostic analysis of three sets of real-time signal propagation loss data obtained over a Long Term Evolution (LTE) mobile broadband network. When compared with the most popular Levenberg–Marquardt (LM), QN, and Gradient Descent (GD) methods, the proposed method achieved the 30–46% precision accuracies over other methods using three different statistical indicators, particularly in two study locations. The indicators are root mean square error, correlation coefficient and mean absolute error. The awesome precision performance of the proposed method can be explored to overcome premature convergence and poor predictive fitting issues often experienced in the identification and tuning-based estimation of the signal propagation loss parameters during or after cellular network planning processes

Studies on the prevalence of Hepatitis C virus infection in diabetic patients attending a tertiary health-care facility South-west Nigeria

Background: Hepatitis C virus (HCV) infection and type 2 diabetes mellitus (T2DM) are two major public health problems associated with increasing complications and mortality rates worldwide. The objective of this study is to evaluate the prevalence of hepatitis C virus (HCV) infection in diabetic patients and to investigate the influence of several epidemiological and clinical factors on HCV infection. Method: A total number of one hundred and eighty diabetic patients were recruited for this study. Consented subjects made up of 71(39.4%) males and 109(60.56%) females were recruited for the study. While one-Hundred (100) Non-Diabetics (Controls) were also recruited for the study. Structured questionnaires were administered to the consented participants to obtain relevant data. Sera samples were assayed for antibodies to HCV using an enzyme linked immunosorbent assay [Inteco Diagnostic Limited]. ELISA technique. Result: Overall prevalence of HCV infection among diabetes patients assayed was 13.3% out of which 8(11.3%) was obtained from the male subjects compared to 16 (14.7%) seropositivity recorded among the females (P = 0.511; P > 0.05). Considering age distribution, Subjects aged 41–50 years recorded, 9 (22.5%) positivity (P = 0.238; P > 0.05).Considering educational status of subjects screened, 22 (14.9%) positivity was rescored among subjects who have attained tertiary status of education.(P = 0.574;P > 0.05).Risk factors considered showed that, 7 (18.9%) seropositive subject were alcoholic consumers(P value = 0.2621;P > 0.05) while 5 (8.9%) recorded history of sharing sharp objects P = 0.2427;P > 0.05). Conclusion: Our study shows a slightly higher prevalence of hepatitis C infection in type 2 diabetics. This call for urgent routine screening exercise among diabetic patients for HCV infection. This study also emphasizes the need for public enlightenment on the association between HCV infection and T2DM, to avert possible complications among diabetic patients