Genotype × environment interactions complicate selection of superior genotypes for narrow and wide adaptation. Eighteen tropically-adapted maize cultivars were evaluated at six locations in Nigeria for 2 yrs to (i) identify superior and stable cultivars across environments and (ii) assess relationships among test environments. Environment and genotype × environment interactions (GEI) were significant (P < 0·05) for grain yield. Environments accounted for 63.5% of the total variation in the sum of squares for grain yield, whereas the genotype accounted for 3.5% and GEI for 32.8%. Grain yield of the cultivars ranged from 2292 kg ha -1 for DTSTR-W SYN2 to 2892 kg ha -1 for TZL COMP4 C3 DT C2 with an average of 2555 kg ha -1 . Cultivar DT SYN2-Y had the least additive main effect and multiplicative interaction (AMMI) stability value of 7.4 and hence the most stable but low-yielding across environments. AMMI biplot explained 90.5% and classified cultivars and environments into four groups each. IWD C3 SYN F3 was identified as the high-yielding and stable cultivar across environments. ZA15, ZA14, BK14, BK15 and IL15 had environment mean above the grand mean, while BG14, BG15, LE14, LE15, IL14, LA14 and LA15 had mean below the grand mean. ZA, BK, BG, LE and LA were found to be consistent in ranking the maize cultivars. However, Zaria, Birnin Kudu, and Ilorin were identified as the best test locations and could be used for selecting the superior maize cultivars. The identified high-yielding and stable cultivar could be further tested and promoted for adoption to contribute to food insecurity in Nigeria.

This article proposed a new distribution referred to as the transmuted odd generalized exponential-exponential distribution (TOGEED) as an extension of the popular odd generalized exponential- exponential distribution by using the Quadratic rank transmutation map (QRTM) proposed and studied by [1]. Using the transmutation map, we defined the probability density function (pdf) and cumulative distribution function (cdf) of the transmuted odd generalized Exponential- Exponential distribution. Some properties of the new distribution were extensively studied after derivation. The estimation of the distribution’s parameters was also done using the method of maximum likelihood estimation. The performance of the proposed probability distribution was checked in comparison with some other generalizations of Exponential distribution using a real life dataset.  

Background Coronary artery disease was hitherto a rarity in Africa. Acute coronary syndrome (ACS) accounts for coronary artery disease–related morbidity and mortality. Reports on ACS in Africa are few. Methods and Results We enrolled 1072 indigenous Nigerian people 59.2±12.4 years old (men, 66.8%) with ACS in an observational multicentered national registry (2013–2018). Outcome measures included incidence, intervention times, reperfusion rates, and 1‐year mortality. The incidence of ACS was 59.1 people per 100 000 hospitalized adults per year, and comprised ST‐segment–elevation myocardial infarction (48.7%), non–ST‐segment–elevation myocardial infarction (24.5%), and unstable angina (26.8%). ACS frequency peaked 10 years earlier in men than women. Patients were predominantly from urban settings (87.3%). Median time from onset of symptoms to first medical contact (patients with ST‐segment–elevation myocardial infarction) was 6 hours (interquartile range, 20.1 hours), and only 11.9% presented within a 12‐hour time window. Traditional risk factors of coronary artery disease were observed. The coronary angiography rate was 42.4%. Reperfusion therapies included thrombolysis (17.1%), percutaneous coronary intervention (28.6%), and coronary artery bypass graft (11.2%). Guideline‐based pharmacotherapy was adequate. Major adverse cardiac events were 30.8%, and in‐hospital mortality was 8.1%. Mortality rates at 30 days, 3 months, 6 months, and 1 year were 8.7%, 9.9%, 10.9%, and 13.3%, respectively. Predictors of mortality included resuscitated cardiac arrest (odds ratio [OR], 50.0; 95% CI, 0.010–0.081), nonreperfusion (OR, 34.5; 95% CI, 0.004–0.221), pulmonary edema (OR, 11.1; 95% CI, 0.020–0.363), left ventricular diastolic dysfunction (OR, 4.1; 95% CI, 0.091–0.570), and left ventricular systolic dysfunction (OR, 2.1; 95% CI, 1.302–3.367). Conclusions ACS burden is rising in Nigeria, and patients are relatively young and from an urban setting. The system of care is evolving and is characterized by lack of capacity and low patient eligibility for reperfusion. We recommend preventive strategies and health care infrastructure‐appropriate management guidelines.

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