Many businesses have been positively impacted by electronic commerce (ecommerce). It has enabled enterprises and consumers transact business digitally and experience diversity as long as the internet ...is accessible and there is a gadget to surf the internet. Several governments have gradually adopted electronic payment throughout the country. The Nigerian government has also done a lot of prodding toward the adoption of a cashless economy, which includes embracing ecommerce. As ecommerce expands, so does actual and attempted fraud through this channel. According to the Nigerian Central Bank, electronic fraud reached trillions of Naira by 2021. The purpose of this work was to employ logistic regression as a decision-making tool for detecting fraud in e-commerce platforms at either the virtual or physical point of sale. The main contribution of this research is a model developed using logistic regression for detecting fraud at the point of sale on electronic commerce platforms. The accuracy of the result is 97.8 percent. The result of this study will provide key decision makers in ecommerce firms with information on fraud patterns on their ecommerce platforms, this will enable them take quick actions to forestall these fraudulent attempts. Further research should be carried out using data from other developing countries.
Genetic variants that underlie susceptibility to cervical high-risk human papillomavirus (hrHPV) infections are largely unknown. We conducted discovery genome-wide association studies (GWAS), ...replication, meta-analysis and colocalization, generated polygenic risk scores (PRS) and examined the association of classical HLA alleles and cervical hrHPV infections in a cohort of over 10,000 women. We identified genome-wide significant variants for prevalent hrHPV around LDB2 and for persistent hrHPV near TPTE2, SMAD2, and CDH12, which code for proteins that are significantly expressed in the human endocervix. Genetic variants associated with persistent hrHPV are in genes enriched for the antigen processing and presentation gene set. HLA-DRB1*13:02, HLA-DQB1*05:02 and HLA-DRB1*03:01 were associated with increased risk, and HLA-DRB1*15:03 was associated with decreased risk of persistent hrHPV. The analyses of peptide binding predictions showed that HLA-DRB1 alleles that were positively associated with persistent hrHPV showed weaker binding with peptides derived from hrHPV proteins and vice versa. The PRS for persistent hrHPV with the best model fit, had a P-value threshold (PT) of 0.001 and a p-value of 0.06 (-log10(0.06) = 1.22). The findings of this study expand our understanding of genetic risk factors for hrHPV infection and persistence and highlight the roles of MHC class II molecules in hrHPV infection.
There has been no previous systematic, epidemiological study of the reproductive risk factors for uterine fibroids (UF) in African populations despite African women having the highest burden of UF in ...the world. Improved knowledge of the associations between UF and reproductive factors would contribute to better understanding of the etiology of UF and may suggest novel opportunities for prevention and therapeutic interventions. We used nurse administered questionnaires to survey the demographic and reproductive risk factors of UF among 484 women who are members of the African Collaborative Center for Microbiome and Genomics Research (ACCME) Study Cohort in central Nigeria, and who had transvaginal ultrasound diagnosis (TVUS). We used logistic regression models to the evaluate associations between reproductive risk factors and UF, adjusted for significant covariates. In our multivariable logistic regression models, we found inverse associations with number of children (OR = 0.83, 95%CI = 0.74-0.93, p-value = 0.002), parity (OR = 0.41, 95%CI = 0.24-0.73, p-value = 0.002), history of any type of abortion (OR = 0.53, 95%CI = 0.35-0.82, p-value = 0.004), duration of use of Depot Medroxyprogesterone Acetate (DMPA) (p-value for trend = 0.02), menopausal status (OR = 0.48, 95%CI = 0.27-0.84, p-value = 0.01), and a non-linear positive association with age (OR = 1.04, 95%CI = 1.01-1.07, p-value = 0.003). Other reproductive risk factors that have been reported in other populations (age at menarche and menopause, and oral contraceptives) were not associated with UF in this study. Our study confirms some of the reproductive risk factors for UF that have been found in other populations and shows that some of them are stronger in the Nigerian population. The associations we found with DMPA suggest opportunities for further research to understand the mechanisms of action of progesterone and its analogues in the etiology of UF, their potential use for prevention and treatment of UF.
Self-report of uterine fibroids (UF) has been used for epidemiologic research in different environments. Given the dearth of studies on the epidemiology of UF in Sub-Saharan Africa (SSA), it is ...valuable to evaluate its performance as a potential tool for much needed research on this common neoplasm in SSA women. We conducted a cross-sectional study of self-report of UF compared with transvaginal ultrasound diagnosis (TVUS) among 486 women who are members of the African Collaborative Center for Microbiome and Genomics Research (ACCME) Study Cohort in central Nigeria. We used log-binomial regression models to compute the classification, sensitivity, specificity, and predictive values of self-report compared to TVUS, adjusted for significant covariates. The prevalence of UF on TVUS was 45.1% (219/486) compared to 5.4% (26/486) based on self-report of abdominal ultrasound scan and 7.2% (35/486) based on report of healthcare practitioner's diagnosis. Self-report correctly classified 39.5% of the women compared to TVUS in multivariable adjusted models. The multivariable adjusted sensitivity of self-report of healthcare worker diagnosis was 38.8%, specificity was 74.5%, positive predictive value (PPV) was 55.6%, and negative predictive value (NPV) was 59.8%. For self-reported abdominal ultrasound diagnosis, the multivariable adjusted sensitivity was 40.6%, specificity was 75.3%, PPV was 57.4%, and NPV was 60.6%. Self-report significantly underestimates the prevalence of UF and is not accurate enough for epidemiological research on UF. Future studies of UF should use population-based designs and more accurate diagnostic tools such as TVUS.
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Background: Cervical cancer is the second commonest cancer in Africa. Persistent High-risk HPV (HRHPV) infection is a necessary cause but little is known about the persistence and ...associated risk factors of HRHPV infection in African women. The aim of this study was to determine risk factors and incidence of HPV infection in Nigerian women. Methods: ACCME is a multicenter prospective cohort study of host germline, cervical somatic and HRHPV genomics, epigenomics, and vaginal microenvironment; and their association with HPV. From February/2014 to January/2016, 10,000 HIV-negative women were enrolled into the cohort and are being followed up every 6 months. We used SPF
25
/LiPA
10
to characterize HPV infection and defined persistent infection as 2 consecutive positive tests done at least 12 months apart. Logistic regression models were used to estimate the associations between risk factors and persistent HPV. Results: The mean (SD) age of the study participants at baseline was 40 (10) years and the mean (SD) vaginal pH was 5.2 (0.6). About 42% of the participants were positive for any HPV positive and 21% had persistence of any HPV infections. Some, 35% of the participants had multiple infections with any HPV. About 54% of those with persistent any HPV infections had HRHPV; HPV types 52 (25%) and 18 (15%) were the most prevalent and persistent HRHPV types. The incidence of any HPV infection was 6.6/1,000 person-months while that of HRHPV was 2.6/1,000 person-months. Age, body mass index, level of education, marital and socio-economic status and total number of lifetime sexual partners were associated with HPV infection in these women. Conclusions: We defined the incidence, risk factors and commonest types of HRHPV in a large cohort of women in West Africa.
Abstract 63
Background:
Cervical cancer is the second most common cancer in Africa. Persistent high-risk human papillomavirus (HRHPV) infection is a necessary cause but little is known about the ...persistence and associated risk factors of HRHPV infection in African women. We undertook this work to determine risk factors and the incidence of HPV infection in Nigerian women.
Methods:
ACCME is a multicenter, prospective cohort study of host germline, cervical somatic and HRHPV genomics, epigenomics, and vaginal microenvironment and their association with HPV. From February 2014 to January 2016, 10,000 HIV-negative women were enrolled in the cohort and are being observed every 6 months. We used SPF
25
/LiPA
10
to characterize HPV infection and defined persistent infection as two consecutive positive tests performed at least 12 months apart. Logistic regression models were used to estimate associations between risk factors and persistent HPV.
Results:
The mean (± standard deviation) age of study participants at baseline was 40 (± 10) years, and mean (± standard deviation) vaginal pH was 5.2 (± 0.6). Approximately 42% of participants were positive for any HPV and 21% had persistence of any HPV infection. Some (35%) participants had multiple infections with any HPV. Approximately 54% of those with persistent any HPV infection had HRHPV—HPV type 52 (25%) and type 18 (15%) were the most prevalent and persistent HRHPV types. Incidence of any HPV infection was 6.6 per 1,000 person-months, whereas that of HRHPV was 2.6 per 1,000 person-months. Age, body mass index, education level, marital and socioeconomic status, and total number of lifetime sexual partners were associated with HPV infection in these women.
Conclusion:
We defined the incidence, risk factors, and most common types of HRHPV in a large cohort of women in West Africa.
AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST
Sally N. Adebamowo No relationship to disclose Michael Odutola No relationship to disclose Ayotunde Famooto No relationship to disclose Eileen Dareng No relationship to disclose Amos Adebayo No relationship to disclose Peter Achara No relationship to disclose Bunmi Alabi No relationship to disclose Kayode Obende No relationship to disclose Richard Offiong No relationship to disclose Sanni Ologun No relationship to disclose Clement A. Adebamowo Speakers' Bureau: Merck
Knowledge of wear resistance properties of newly emerging materials as complements to their mechanical properties is important to broaden their applications. This study focuses on wear resistance ...properties of particle-reinforced epoxy. Results obtained reveal that surface wear of the examined epoxy-based composites occurred by the crack initiation by the abrasive tips of the wear tester, crack propagation and/or crack pinning. Linear regression model has accuracies of 99.94, 99.92, 99.93, 99.88, 99.91 and 99.92% with respect to various grades of composites examined. Response surface two-functional interaction model exhibits a better goodness of fit than the response surface linear model that shows an outlier. The response surface linear model best fits the wear rates of AlnpUCSnp/epoxy and AlnpCCSnp/epoxy with respective adequate precision of 14.138 and 10.204 affirming the model’s adequate signal. Hence, this study establishes that epoxy-based hybrid composite having 4.7%–82.47 nm-sized aluminium-5.76%–49.85 nm-sized carbonised coconut shell hybrid particles experiences a surface wear of 0.00272721 g per metre when it is in contact with a rough surface under an applied load of 16.71 N at a speed of 0.7 ms
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In educational data mining, the process of analysing and predicting from a pool of acquired data is a big challenge due to the influence of behavioural, environmental, parental, personal and social ...traits of students. While existing education predictive systems have used patterns generated from mined common factors to predict student performance based on subject, faculty, and grade amongst others, explicit traits, which defines a student are often neglected. Thus, such existing models are too general for specific and targeted analysis in more recent times when predictive features are although common but in real essence unique to individual students to a certain degree. Here, a Self-Academic Appraisal and Performance Predictive (SAAPP) system was developed to analyse and predict the overall performance of students before the expiration of their course duration. The inherent knowledge driven model analyses common available predictive internal and external factors, with probabilistic analysis of student academic history and pending courses. The system then builds a personal data centric system for individual student through a decision support expert system and a probabilistic optimal grade point analysis for more effective recommendation. The developed system is more accurate, reliable and precise in student performance classification with targeted recommendations.
Nigerians have a notable online presence and actively discuss political and topical matters. This was particularly evident throughout the 2023 general election, where Twitter was used for ...campaigning, fact-checking and verification, and even positive and negative discourse. However, little or none has been done in the detection of abusive language and hate speech in Nigeria. In this paper, we curated code-switched Twitter data directed at three musketeers of the governorship election on the most populous and economically vibrant state in Nigeria; Lagos state, with the view to detect offensive speech in political discussions. We developed EkoHate -- an abusive language and hate speech dataset for political discussions between the three candidates and their followers using a binary (normal vs offensive) and fine-grained four-label annotation scheme. We analysed our dataset and provided an empirical evaluation of state-of-the-art methods across both supervised and cross-lingual transfer learning settings. In the supervised setting, our evaluation results in both binary and four-label annotation schemes show that we can achieve 95.1 and 70.3 F1 points respectively. Furthermore, we show that our dataset adequately transfers very well to three publicly available offensive datasets (OLID, HateUS2020, and FountaHate), generalizing to political discussions in other regions like the US.
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