Course Gaps at Bauchi State University

This course reviews social determinants of health. How education status, social status and economic status affects health. Sociological perspective of health. The functionalist approach, the conflict approach, and the interactionist approach. The social issues in health with reference to the services offered such as social welfare services, care of the motherless babies, care, and rehabilitation of the handicapped, care of the elderly and the care of destitute/beggars are discussed. Inequality and social class in relation to health. Ethnicity. gender and health. Health equity and social stigmatisation are taught.

Introduction to immune system: Definitions, types (adaptive and innate), B and T lymphocytes, chemical mediators (cytokines, interleukenes, antibodies, and many others). Abnormal immune responses: Hypersensitivity (Type I, II, III, IV), Autoimmunity, immunodeficiency diseases. Immunosuppressive drugs: Glucocorticoids, Calcineurin inhibitors, Anti-proliferatives (mycophenolate e.t.c), cytotoxic agents, Antibodies, RhO (D) immune globulin, Monoclonal antibodies, (rituximab and many others). Cytokines: Interferones, TNF – alpha, and many others. Drug allergy, Tumor markers for solid tumors. Antigraft rejection drugs. Steroidal and non- steroidal anti-inflammatory drugs. Used in the treatment of gout. Practical: Designed to reflect experimental models of the topics taught above.

This is an introductory course on Artificial Intelligence. The topics include; Overview: foundations, scope, problems, and approaches of AI. Intelligent agents: reactive, deliberative, goal-driven, utility-driven, and learning agents; Artificial Intelligence programming techniques. Problem-solving through Search: forward and backward, state-space, blind, heuristic, problem-reduction, A, A*, AO*, minimax, constraint propagation, neural, stochastic, and evolutionary search algorithms, sample applications. Knowledge Representation and Reasoning: ontologies, foundations of knowledge representation and reasoning, representing and reasoning about objects, relations, events, actions, time, and space; predicate logic, situation calculus, Content logics, reasoning with defaults, reasoning about knowledge, sample applications. Planning: planning as search, partial order planning, construction and use of planning graphs. Representing and Reasoning with Uncertain Knowledge: probability, connection to logic, independence, Bayes rule, bayesian networks, probabilistic inference, sample applications. Decision-Making: basics of utility theory, decision theory, sequential decision problems, elementary game theory, sample applications. Machine Learning and Knowledge Acquisition: learning from memorisation, examples, explanation, and exploration. learning nearest neighbor, naive Bayes, and decision tree classifiers, Q-learning for learning action policies, applications. Sample Applications of AI, student project presentations.

Pattern of transmission of single gene trait. Hardy-Weinberg Law Conditions for its Validity, application. On concepts of continuous and discontinuous variation. Pharmacogenetics (drug metabolism, tissue metabolism and receptor alterations). Compartment models (one and two) kinetics after intravenous and oral dosing. Bioavailability, Drug distribution, Protein binding. Renal excretion of drugs. Urinary excretion data in Pharmacokinetic analysis.

Concepts of entrepreneurship, entrepreneurial knowledge, skills and attitudes needed in the 21st century in the field of Physiology, definition of small business, strengths and weaknesses of small business, trends expected of small businesses, ethics and social responsibility - the role that values play in ethical behaviour and the importance of ethics; ethics versus social responsibility, the business plan in Physiology; the need for a business plan, the steps in the preparation of a business plan and financial plans, location of a business in Physiology; importance of site selection for a business, processes for selecting the right site for a business, financing a business in Physiology; estimating the money needed to launch a new business, ways to raise money for a new business, organizational planning for a business in Physiology; staffing. training and organizational charts.

Introduction: Drug – receptor interaction; affinity and [intrinsic activity; occupancy theory; Rate Theory; Drug receptor interactions; law of mass action, enzyme-substrate interaction. dose- response relationship – Graphical and Derivation of receptor affinity PD2; Competitive Antagonism. The Gaddum-Schild Equation for Affinity constant of competitive antagonists; Non-competitive antagonism, Partial agonist; Competitive non-competitive antagonism. Pharmacodynamic prediction from pharmacokinetic data (one compartment model). Receptor desensitisation, Mechanisms of Post-receptor transduction. Introduction to Biostatistics, Normal distribution, Mean probit transformation, standard Deviation and standard Error. T-tests paired and unpaired, chi- square Test, Analysis of variance, Poisson Distribution. Physiology and Pharmacology courses are the minor and major courses in a BSc Pharmacology programme worldwide. Students must therefore be well grounded in them upon graduation to be able to pursue a successful career. Physiology provides the theoretical basis of normal body function while pharmacology explains how drugs and chemicals exert correction in situations of altered physiology. These two courses transverse all organs/systems of the human body and span 200 to 400 Levels of the BSc Pharmacology programme.

This course focuses on the interface between society and the product of art. How art serves the needs of society and the aesthetic dimensions of art, the democracy of art, the role of art in the education process, art and the ethics of living art as a product of culture, art and meaning in society Issues of culture and art education; examination of various forms of art as representations of knowledge, belief and Pierre Bourdieu’s concept of habitus, art as symbolic and cultural capital. Epistemology, the meaning of function, and the conceptual location of visual culture in society.

Uses of computers in statistical computing. Introduction to various statistical packages. Use of statistical packages in solving problems in statistics. spread sheet applications. Such as SPSS, STATA, MINITAB. can be used to demonstrate statistical methodology.

Population and samples. Asymptotics. Statistical models and methodologies. Random sampling distributions. Elementary time series analysis. Index numbers. Demographic measures. Estimation (point and interval) and tests of hypotheses concerning population mean and proportion (one and two sample cases). Regression and correlation. Programming in Python computer language. Computation of mean, variance and correlation. Sorting and ranking of data. Data Step Processing. Preparing Data for Analysis. Evaluating Quantitative Data. Sample Size Estimation. Basic statistical computing in regression analysis and the analysis of designed experiments. Introduction to Monte Carlo methods. Use of statistical packages like SPSS, SAS, Minitab, GENSTAT, EPI-INFO, SYSTAT. Lab work: Practical experiments on statistical models and methodologies. Practical exercises on random sampling distribution methods. Practicals on test of hypothesis, population, mean, proportion, regression and correlation analysis. Exercise on how to sort and data from different data set. Use of SPSS for data analysis and computation.

To advance the knowledge of recreation and (R&T), attributes and categorization of (R & T) resources, infrastructure services and participation, socio-economic evaluation and the ecological impacts. Definition and Concept. Nature and classification of tourism resources and recreational land uses. Water base (R&T) Land base (R&T). Urban and Rural distributions Infrastructure and services. Administration and Management of (R & T). The positive and negative impacts of Recreation and Tourism.