A Survey of Facebook Usage in North East of Nigeria

The study is on a survey of Facebook usage in the North Eastern Nigeria. The objective of the research is to find out the level of usage of Facebook in the North Eastern States of Nigeria. The study find out that majority 198(66.00%) of the respondents said they accessed their Facebook account daily. Minority 2(0.67%) of the respondents said they accessed their Facebook account monthly. Majority 105(35.00%) of the respondents said they used their Facebook account for communicating with friends only. While minority 16(5.35%) of the respondents said they used their Facebook accounts for communicating with friends and for relationship. The findings further revealed that majority 118(39.33%) of the respondents said the type of people they meet on Facebook were friends, college mates and family members, while minority 4(1.34%) of the respondents said the type of people they meet on Facebook were close friends and people that are not known to them. Majority 149(49.67%) of the respondents said the challenges they encountered in the use of Facebook was low internet speed. The study recommends among otherthings that, government should mandate the internet providers to switch over from G3 to G4,  This way the problem of low internet speed would be a thing of the past. The study then concluded that, all Facebook users no matter their age, sex, and cultural background have one thing in common, that is, they use the platform to communicate with their friends and loved ones. Keywords: Communication, Facebook, Friendship, Internet &Social medi

The Effect of Formulation Variables on the Release Kinetics of Paracetamol Tablet Formulations.

Aim: The objective of this work was to study the effects of formulation variables on the release kinetics of paracetamol tablet formulation. Materials and Methods: Paracetamol tablets were formulated using wet granulation (WG) and direct compression (DC) using two predetermined pressures. Avicel, dicalcium phosphate (DCP) and pregelatinized starch (PGS) were used as directly compressible excipients for the DC method while corn starch, gelatin and acacia were used as binders for the WG methods. Tensile strength (TS) and the dissolution times of the tablets were determined. The drug release data were fitted into different kinetic models to determine the drug release mechanism(s) for the paracetamol tablets. Noyes-Whitney plots were further used to obtain release processes for formulations having r2 of best fit from kinetic modeling. Results and Discussion: The TS and dissolution times increased with increase in compressional pressure for all tablet formulations. The ranking of TS for tablets was starch > gelatin > acacia > avicel > DCP > PGS. Drug release kinetics indicated that the drug release was best explained by first order model for direct compression formulation. However, first-order and Higuchi equations gave the best fit with the highest correlation coefficient for the formulation prepared through wet granulation. Korsmeyer’s plots indicated an n value ranging from 1.227 to 1.839 which indicates that the drug release mechanism from the formulations was by super case II transport. Generally, r2 values were higher for tablets with lower compression pressures and higher for those with binders than direct compression excipients. Conclusion: The release kinetics of paracetamol tablets were observed to be influenced by the interplay of variables involved like compressional pressure, formulation excipient and method. Wet granulation was also found to produce optimum release than direct compression

Comparison of PCR-based detection of Plasmodium falciparum infections based on single and multicopy genes

PCR-based assays are the most sensitive and specific methods to detect malaria parasites

Technology usage and employee behaviour: controversies, complications, and implications in the Nigerian business environment

Organizations are among the key units of the society. An organization comprises of several people including employees. The behaviour of employees determines the performance and efficiency of the organization. Technology is an important factor that distinguishes one organization from the other. Employee’s acceptance, rejection, and adaptability to technology being used determine to a great extent how organizations will thrive in a business environment. The drive of technology usage is to ensure that work processes are made easier, faster and to improve the organization’s economic efficiency. In addition, technology usage greatly influences employee behaviour. The aim of this paper is to find out how technology usage affects employee behaviour and vice versa. It is important to understand that in order to improve employee’s usage of technology incorporated into the organization, individual behaviour of employees must be examined cum their attitude. The results of the study indicate that employee behaviour mainly affects technology usage, promotes individual learning, increases efficiency and effectiveness, and improves organizational performance. The paper therefore recommends periodic review of organizational policies and in addition, procure hardware and software to guide against hackers and scammers to avoid losing those important informatio

Comparison of formation of visco-elastic masses and their properties between zeins and kafirins

Zeins of differing sub-class composition much more readily formed visco-elastic masses in water or acetic acid solutions than equivalent kafirin preparations. Visco-elastic masses could be formed from both zein and kafirin preparations by coacervation from glacial acetic acid. Dissolving the prolamins in glacial acetic acid apparently enabled protonation and complete solvation. Stress-relaxation analysis of coacervated zein and kafirin visco-elastic masses showed they were initially soft. With storage, they became much firmer. Zein masses exhibited predominantly viscous flow properties, whereas kafirin masses were more elastic. The γ-sub-class is apparently necessary for the retention of visco-elastic mass softness with kafirin and zein, and for elastic recovery of kafirin. Generally, regardless of water or acetic acid treatment, all the zein preparations had similar FTIR spectra, with greater α-helical conformation, than the kafirin preparations which were also similar to each other. Kafirin visco-elastic masses have a much higher elastic character than zein masses.http://www.elsevier.com/locate/foodchem2019-04-15hj2018Food Scienc

Towards a more efficient and cost-sensitive extreme learning machine: A state-of-the-art review of recent trend

In spite of the prominence of extreme learning machine model, as well as its excellent features such as insignificant intervention for learning and model tuning, the simplicity of implementation, and high learning speed, which makes it a fascinating alternative method for Artificial Intelligence, including Big Data Analytics, it is still limited in certain aspects. These aspects must be treated to achieve an effective and cost-sensitive model. This review discussed the major drawbacks of ELM, which include difficulty in determination of hidden layer structure, prediction instability and Imbalanced data distributions, the poor capability of sample structure preserving (SSP), and difficulty in accommodating lateral inhibition by direct random feature mapping. Other drawbacks include multi-graph complexity, global memory size, one-by-one or chuck-by-chuck (a block of data), global memory size limitation, and challenges with big data. The recent trend proposed by experts for each drawback is discussed in detail towards achieving an effective and cost-sensitive mode

Correction to: Thermal decomposition of rice husk: a comprehensive artificial intelligence predictive model

Unfortunately, in the original publication of the article the third author name was misspelled as Faisal Abnisal. The corrected author name should read as “Faisal Abnisa”. The affiliation of third author was incorrectly published. The corrected affiliation is given below

Thermal decomposition of rice husk: a comprehensive artificial intelligence predictive model

This study explored the predictive modelling of the pyrolysis of rice husk to determine the thermal degradation mechanism of rice husk. The study can ensure proper modelling and design of the system, towards optimising the industrial processes. The pyrolysis of rice husk was studied at 10, 15 and 20 °C min−1 heating rates in the presence of nitrogen using thermogravimetric analysis technique between room temperature and 800 °C. The thermal decomposition shows the presence of hemicellulose and some part of cellulose at 225–337 °C, the remaining cellulose and some part of lignin were degraded at 332–380 °C, and lignin was degraded completely at 480 °C. The predictive capability of artificial neural network model was studied using different architecture by varying the number of hidden neurone node, learning algorithm, hidden and output layer transfer functions. The residual mass, initial degradation temperature and thermal degradation rate at the end of the experiment increased with an increase in the heating rate. Levenberg– Marquardt algorithm performed better than scaled conjugate gradient learning algorithm. This result shows that rice husk degradation is best described using nonlinear model rather than linear model. For hidden and output layer transfer functions, ‘log-sigmoid and tan-sigmoid', and ‘tansigmoid and tan-sigmoid' transfer functions showed remarkable results based on the coefficient of determination and root mean square error values. The accuracy of the results increases with an increasing number of hidden neurone. This result validates the suitability of an artificial neural network model in predicting the devolatilisation behaviour of biomass

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe