University of Ibadan Journals
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Disruption of Phloem Transport by the two South African Biotypes of the Russian Wheat Aphid [Diuraphisnoxia Kurdjumov (Homoptera: Aphididae)] Feeding on Barley (Hordeumvulgare L.)
Get PDFWe investigated the comparative effects of the feeding of two South African biotypes of the Russian wheat aphid (RWA, DiuraphisnoxiaKurdjumov), RWASA1 and RWASA2, on the phloem transport functionality of three selected exotic RWA-resistant barley (Hordeumvulgare L.) lines. RWASA2 is known to breed faster and as a more aggressive feeder, causing more severe damage than RWASA1 on host plants. We examined the phloem transport capacity of the barley lines, using the phloem-mobile fluorophore, 5,6-carboxyfluorescein diacetate (5,6-CFDA).Feeding by the newly-emerged more aggressive RWASA2 biotype caused a more marked decrease in phloem transport capacity, compared to RWASA1, during both short- and long-term feeding exposure. The extensive phloem damage was mirrored in a significant reduction in transport capacity in non-resistant PUMA, but not to the same extent in the USDA lines, indicative of reduced resistance when these lines were subjected to the South African RWA biotypes. The resistant lines should therefore be explored in breeding programmes for development of RWA-resistant barley lines in South Africa
Air and heavy metal pollution around a steel foundry in Ogijo, Ogun State, Nigeria
Get PDFA whole range of bye-products from industries such as steel plants and metal processing facilities create serious pollutionto the environment, with negative health implications. In this study, we examined environmental pollution around AfricanSteel Foundry in Ogun State, Nigeria. Air sampling was carried out using Land Duo Multi gas monitor to determine airpollutants such as Total Suspended Particulate Matter (TSP), Carbon monoxide (CO), Carbon dioxide (CO2), Nitrous oxide(NO), Nitrous oxide and Nitrogen dioxide (NOx), Hydrogen sulphide (H2S) and Sulphur dioxide (SO2). Thirty soil and plantsamples were collected from Steel Foundry. Concentrations of selected heavy metals (Fe, Cu, Cd, Ni and Pb) weredetermined in both soil and plant (cassava, pawpaw and maize leaves) samples using an Atomic Absorption Spectroscopy(AAS). The results show that total suspended particulate matter (TSP) ranged from 123.46 ?gm–3-353.74 ?gm–3, while CO,CO2, NO, NOx, H2S, and SO2 ranged from 3.20-13.33 ppm, 3.55-5.04 ppm, 1.36-5.69 ppm, 2.02- 8.50 ppm, 0.96-1.93 ppm and1.63-3.96 ppm respectively. Some of these values exceeded the USEPA guideline limit of clean air. Mean concentrations ofFe, Cu, Cd, Pb and Ni found in the plants and soils were below WHO guideline limit of heavy metals. The results revealedthe high concentration TSP, NO, and SO2 which may lead to health risk after long time of exposure and also accumulationof these metals overtime may lead to contamination of the agricultural soils which eventually pose threat to organisms thatfeed on the plants
A comparative analysis of the binding site of Plasmodium falciparum histone deacetylase-1 and human histone deacetylase-8
Get PDFHistone deacetylases (HDACs) are a family of enzymes involved in the modulation of mammalian cell chromatin structure,regulation of gene expression, DNA repair, and stress response. The histone deacetylase enzymes Plasmodium falciparumhistone deacetylase-1 (PfHDAC-1) and human histone deacetylase-8(hHDAC 8) have been identified as novel targets fordevelopment of antimalarial and antitumor drugs respectively. Homology models of PfHDAC-1 and hHDAC 8 weregenerated from the crystal structures of HDAC8 and HDLP and IT64 respectively using a restraint guided optimizationprocedure involving a combination of the Optimized Potentials for Liquid Simulations and the Generalized Born SurfaceArea (OPLS/GBSA) potential setup. The models were validated using protein structure validation tools. Comparativeanalysis of their binding sites was also carried out to identify their topology and residue interaction that could be utilizedin developing PfHDAC-1 specific inhibitors
A comparative analysis of the binding site of Plasmodium falciparum histone deacetylase-1 and human histone deacetylase-8
Get PDFHistone deacetylases (HDACs) are a family of enzymes involved in the modulation of mammalian cell chromatin structure,regulation of gene expression, DNA repair, and stress response. The histone deacetylase enzymes Plasmodium falciparumhistone deacetylase-1 (PfHDAC-1) and human histone deacetylase-8(hHDAC 8) have been identified as novel targets fordevelopment of antimalarial and antitumor drugs respectively. Homology models of PfHDAC-1 and hHDAC 8 weregenerated from the crystal structures of HDAC8 and HDLP and IT64 respectively using a restraint guided optimizationprocedure involving a combination of the Optimized Potentials for Liquid Simulations and the Generalized Born SurfaceArea (OPLS/GBSA) potential setup. The models were validated using protein structure validation tools. Comparativeanalysis of their binding sites was also carried out to identify their topology and residue interaction that could be utilizedin developing PfHDAC-1 specific inhibitors
EVALUATING THE EFFECTIVENESS OF THE SKILLS ACQUISITION PROGRAMMES FOR SCHOOL DROP-OUTS IN NIGERIA
Get PDFThe Nigerian society today is filled with school-age children – particularly teenagers – who are supposed to be in school but are found on the streets offering some services to anybody that is interested. Some of these out-of-school children especially school dropouts claimed to have acquired some form of skills at some skills acquisition centres run by the government, private individuals and non-governmental organisations. There is therefore a need for an in-depth evaluation of the effectiveness of skill acquisition programmes. The result revealed that the skill acquisition programmes were ineffective at meeting the needs of the school dropouts
PEDAGOGICAL SYNTHESIS AND EFFECTIVENESS OF INSTRUCTIONAL TECHNOLOGIES IN THE DELIVERY OPEN AND DISTANCE LEARNING PROGRAMME
Get PDFThis paper describes vividly the various forms of instructional technologies as well as the generation of communication technologies available for the delivery of distance education programmes. This is premised on the belief that policy planners and practitioners in distance education need to possess in-depth knowledge of these technologies so as to guide them on the choice of the most appropriate technology to adopt in the delivery of distance education programmes. The paper also discusses the pedagogical effectiveness of each technology in relation to these programmes. This is also premised on the belief that the more familiar tutors are with instructional technologies, the more effective their will be. This was concluded with the criteria that distance education practitioners and managers can adopt or rely upon in the choice of the most appropriate technology in the delivery of distance education programmes with particular reference to Nigeria
STUDENTS’ FACTORS AND EXAMINATION MALPRACTICE IN PUBLIC SECONDARY SCHOOLS IN SOUTH-WEST NIGERIA: IMPLICATIONS FOR POLICY AND PRACTICE
Get PDFThis study investigated the combined and relative effects of six students’ factors (age, gender, peer influence, attitude to examination, attitude to learning and time management) on examination malpractice in public secondary schools in South-West, Nigeria. The participants were two hundred and fifty SSS2 students randomly selected from twelve secondary schools in Southwestern zone of Nigeria. Their ages ranged between 14 and 18years (x = 14.04 and SD = 1.78. Of the sample selected, one hundred and thirty five were boys (135) and one hundred and fifteen were girls (115). A validated instrument, Student Factors Questionnaire (SFQ) was used to collect data for the study using multiple regression for analysis. There was a significant correlation among the six student variables and the dependent variable –examination malpractice (R=0.424; p>0.05). The six variables accounted for the 14.2% of the total variance in the depended measure (R2=0.142) Peer influence (?=0.321; t=3.186; p<0.05), attitude to examination (?=-0.191; t =2.343; p<0.05, time management (?=-0.195; t=2.162; p<0.05) and attitude to learning (?=-0.086; t=2.162; p<0.05) could be used to predict examination malpractice. Results show that examination malpractice cut across age and gender. The result also shows that students’ attitude to peers, examination, learning and time management are the most potent predictors of examination malpractice. Based on the implication of the findings, parents and teachers should help students to develop positive attitude to learning and writing examination through re-orientation of values and reconstruction of students’ attitude to hard work
Detecting Hate Speech on Social Media Using Deep Learning Techniques
Get PDFAbstract Hate speech is a recurring issue on social media platforms identified as an attack against a specific group of people based on certain common characteristics. As online data is created at a very fast rate by users, it has now become a daunting task to manually moderate the comments of users containing hate speech in a bid to reduce its negative effects on a platform. Previous works have been able to create models capable of detecting hate speech with good accuracy on hate speech detection on user comments and posts (known as tweets) on Twitter social media platform. Despite the good results obtained, this kind of models perform poorly when exposed to tweets that contained clever wordings, alternate spellings and rare words. Therefore there is a need to improve the model for the detection of hate speech in user comments on social media in order to address these problems. An ensemble model was developed from two baseline classifiers, NBSVM (Naive Bayes Support Vector Machine ) and LSTM (Long Short Term Memory); combining the power of two well- known performing models from machine learning and deep learning using FastText embeddings from Facebook to improve hate speech detection even when clever wordings, alternate spellings and out of vocabulary words are used. This work was able to improve on the current state of the art hate speech detection by considering OOV (Out Of Vocabulary) words, clever and alternative spellings of words in developing a model that performed better than previous research works in detecting hate speech. The developed ensemble model proved to be able to detect hate speech even when clever wordings, alternate spellings and rare words were used in tweets. There was also an increase in the performance of the model’s hate recall (77%) as compared to the existing popular work of Davidson et. al, (2017) hate recall (61%)
Development of English to Yoruba Machine Translator, Using Syntax-based Model
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Machine translators are required to produce the best possible translation without human assistance. Every machine translator requires programs, automated dictionaries, and grammars to support translation. Studies have shown that the fluency of machine translators depends on the approach or model adopted for their respective developments. Machine translators do not simply involve substituting words in one language for another, but the application of complex linguistic knowledge to decode the contextual meaning of the source text in its entirety. Approaches to machine translators are divided into a single and hybrid approach. In the aim to improve on translation quality of existing English to Yoruba language translator systems, this paper adopts a syntax-based hybrid approach for translating sentences. The grammar for translation is designed and tested with Joshua (an open-source natural language toolkit). The procedure includes data collection, data preparation, data preprocessing, parsing, training of translation model, extract grammar rule, implement grammar, evaluate translations using bilingual evaluation understudy metrics. This paper discusses the translation quality of machine translators (precisely phrase-based and syntax-based) in both tabular and graphical representations. It was observed that a syntax-based translator seemly has higher translation quality than phrase-based
An Integrated Multi-Dimensional Data Warehouse for University Payroll Management
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Payroll is traditionally the most data driven function relating to employee information. The challenge for many large organizations lies in the fragmented nature of payroll. Payroll data generally sits siloed or isolated in a multitude of different local systems. The implication of this is very frustrating: Given the time- consuming manual labour involve in aggregating the payroll data. The lack of integrated consolidated payroll data in a single location as well as the functional arrangement of these data makes it difficult to access timely information and carry out effective analysis to support management decision. This work presents an integrated multi-dimensional data model for a University Payroll System. The model integrates all disparate silos of payroll data sources into a single location for ease and speed of reporting and efficient analysis. The model was simulated and tested using Talend Open Source Data Integration tool while MySQL was used for data storage. Reports were developed from the integrated multi-dimensional data warehouse using a reporting tool, and performance was evaluated and compared relative to same reports generated directly from the various disparate payroll systems. The time it takes to obtain reports from the integrated data warehouse was a lot faster and lot easier than having to obtain same reports from each payroll system and manually aggregating the reports from each of the multiple disparate payroll systems. One obvious reason is that all data in are now integrated in a single location instead of wasting time traversing various payroll data sources. In conclusion, the integrated multi-dimensional data warehouse for payroll system will improve information access, reduce drastically the time to reconcile and obtain reports and provide for far more efficient information analysis for decision makers in the University to make effective strategic decisions based on fact