Fuzzy-based dosage model of aqueous decoction of Adansonia digitata for the management of sickle cell anaemia patients in African Traditional Medicine

In recent time, fuzzy logic-based systems have been deployed in the area of orthodox medicine; especially in situations where precision is most valuable such as kidney transplant, diagnosis of ailments, drug prescription, etc. However, in the area of traditional medicine, no much attention has been given to its enhancement with the use of information technology especially in the area of herbal prescription. In this study, a fuzzy logic-based system is presented, which is used to simulate a prescription model for determining the precise herbal dose suitable for the management of patients suffering from Sickle Cell Disease (SCD). Data on the management of SCD patients were collected from forty Traditional Medical Practitioners (TMPs) at four different local government areas of Edo State, Nigeria. The mass of herb and volume of solvent were used as input parameters to design the dosage model, and simulated using MATLAB. The Fuzzy Inference System (FIS) results obtained for some patients were compared to the prescription given by the TMPs. The results show that the model will eliminate the ordeals of imprecision associated with the management of SCD patients in Nigeria using herbs.Keywords: African Traditional Medicine, Traditional Medicine, Traditional Medical Practitioners, Sickle Cell Disease, Fuzzy logic, Measuremen

A dataset for predicting Supreme Court judgments in Nigeria

It has been widely argued among researchers that the application of big data analytics promises to reduce human bias and provide a scientific and evidence-based approach to the judicial process. In this dataset, historical data consisting of appeal cases presented at the Supreme Court of Nigeria (SCN) were collected from an online repository (Primsol Law Pavillion). A total of 5585 appeal cases brought before the SCN were collected from the archive. The dataset consisted of both criminal and civil appeal cases brought before the SCN. Variables that are related to court case proceedings were identified from related literature, verified by legal experts and used as a basis for generating an electronic structured version of the dataset stored as a spreadsheet file from the unstructured data. From the collected data, thirteen input variables were identified with one output/decision variable. The distribution of the numerical variables was presented as a descriptive statistical summary in terms of the minimum, maximum, mode, mean and standard deviation. The developed dataset can assist researchers to build predictive systems by training their models. Various feature extraction techniques can also be applied on the dataset to remove irrelevant or redundant features for increased performance of such classifiers that are needed to predict the outcome of legal cases

The impact of flooding on Nigeria’s sustainable development goals (SDGs)

Nigeria has Africa’s biggest economy and a population of over 200 million people. Nigeria faces numerous challenges as it struggles to achieve the Sustainable Development Goals (SDGs) with flooding being the most serious with wide-reaching impacts. This paper highlights the impact flooding has on Nigeria reaching SDGs and enumerates the specific SDGs most directly impacted. A systematic literature review provides an overview of the relationship between flooding in Nigeria and the SDGs. It highlights the main causes of Nigeria’s flooding problem are man-made and advocates spatial planning as a suitable Flood Risk Management (FRM) strategy for the Nigerian environment. The paper calls for collaborative action by all concerned stakeholders to address the flooding problem and to help move Nigeria closer to meeting the United Nations (UN) 2030 SDGs. Most importantly, the evidence presented in this paper seeks to promote action on a national scale to combat the flooding in Nigeria and help the nation work more effectively toward achieving the SDGs