Determining house price for mass appraisal using multiple regression analysis modeling in Kaduna North, Nigeria

The research applied Multiple Regression Analysis (MRA) in estimating house price for mass appraisal in Kaduna north, Nigeria. Two basic micro determinants of house price were considered, namely; structural attributes and location of property. Using a sample of 106 house sale transactions data which were recorded between 2011 to 2015, MRA was used to determine the structural variables and locational attributes that have statistically significant influence on the house price. It was found that among the variables included in the MRA, year of transaction, type of house, availability of swimming pool, availability of security post, type of door and location of the property were significant in determining house price in Kaduna. However, number of bedroom, number of living room, type of ceiling, condition of the house were not significant in influencing house price. Using the significant variables, a mass appraisal model was developed for the study area. The performance of the model was evaluated using the ratio study method and the model was found to be satisfactory. It was recommended that, this model be used in mass appraisal of residential properties in Kaduna north in the future, with a view to improve accuracy, objectivity, efficiency, and fairness of the property taxation system, which will lead to generating more revenue for the government and, encourage physical infrastructural development in Kaduna North.Keywords: Mass Appraisal, Multiple Regression Analysis (MRA), House Price, Valuatio

Wind Power Generation in Sudano-Sahelian Region of Nigeria: a Review

Over a couple of years, the world's energy demand has turned to renewable energy sources due to the menace of global warming, while some African countries still depend on fossil fuels despite their harmful effects. Out of approximately 4 trillion (kWh) of renewable energy that is expected to be generated by the year 2030, wind energy is projected to contribute up to 1.1 trillion (kWh). Wind energy studies will be the centre for future renewable engineering efforts, being one of the most likely economic and affordable alternate energy sources. Furthermore, wind resources analysis has also revealed that the Northern part of Nigeria, which occupies almost all the meteorological locations in the Sudano-Sahelian Ecological Zone, possesses enormous potential for harvesting wind energy. This paper involves a systematic review of relevant literature to identify the outcome of various initiatives of researchers at appraising the prospects of electricity production from wind for sustainable development in the region. It was established that the area is blessed with enormous opportunities for harnessing wind for various applications, having possible average wind speeds reaching as high as 8.70 m/s at 10 m above the ground. The region can adequately utilize wind for power generation if the fundamental challenges facing wind energy utilization are addressed. There is a need to systematically model and simulate the system's feasibility before actual implementation to assist in other managerial and technical decisions. Wind energy integration will immensely contribute to providing lasting solutions to the energy situation in the region and the country at large

Immunoinformatic design of a putative multi-epitope vaccine candidate against Trypanosoma brucei gambiense

Human African trypanosomiasis (HAT) is a neglected tropical disease that is caused by flagellated parasites of the genus Trypanosoma. HAT imposes a significant socio-economic burden on many countries in sub-Saharan Africa and its control is hampered by several drawbacks ranging from the ineffectiveness of drugs, complex dosing regimens, drug resistance, and lack of a vaccine. Despite more than a century of research and investigations, the development of a vaccine to tackle HAT is still challenging due to the complex biology of the pathogens. Advancements in computational modeling coupled with the availability of an unprecedented amount of omics data from different organisms have allowed the design of new generation vaccines that offer better antigenicity and safety profile. One of such new generation approaches is a multi-epitope vaccine (MEV) designed from a collection of antigenic peptides. A MEV can stimulate both cellular and humoral immune responses as well as avoiding possible allergenic reactions. Herein, we take advantage of this approach to design a MEV from conserved hypothetical plasma membrane proteins of Trypanosoma brucei gambiense, the trypanosome subspecies that is responsible for the west and central African forms of HAT. The designed MEV is 402 amino acids long (41.5 kDa). It is predicted to be antigenic, non-toxic, to assume a stable 3D conformation, and to interact with a key immune receptor. In addition, immune simulation foresaw adequate immune stimulation by the putative antigen and a lasting memory. Therefore, the designed chimeric vaccine represents a potential candidate that could be used to target HAT

Cervical cancer awareness, perception, and attitude among tertiary health institution students in northeastern Nigeria

BackgroundThe devastating scourge of cervical cancer in Africa is largely due to the absence of preventive interventions, driven by low awareness and poor perception of the disease in the continent. This work is a preliminary effort toward understanding key social drivers promoting this disease in our immediate environment with a view to mitigating it.MethodFemale students of two tertiary health institutions in Azare, northeastern Nigeria, were approached to participate in this cross-sectional descriptive study. A structured self-administered questionnaire was administered to consenting participants and covered questions on their socio-demographics, awareness, perception, and attitude about/toward cervical cancer and its prevention. The responses were scrutinized for coherency and categorized into themes using summary statistics, while a chi-square test was used to determine the association between awareness of cervical cancer and participant age, marital status, religion, screening uptake, and willingness to undergo screen.ResultsAwareness of cervical cancer was recorded among 174/230 (75.7%) respondents who enrolled in this study; 117 (67.2%) knew that it was preventable, but only three (1.3%) respondents had undergone screening. Among the aware participants, 91 (52.3%) and 131 (75.3%) knew that sexual intercourse and multiple sexual partners are risk factors for the disease, respectively. In contrast, knowledge of the etiology was poor; 82 (47.1%) respondents who knew it was preventable had heard about human papillomavirus (HPV), while 72 (41.4%) knew that HPV causes cervical cancer. Most (78%) of the participants expressed willingness to take a human papillomavirus vaccine or undergo screening (84.6%) if made available to them. Awareness was significantly associated with participants’ age (p = 0.022) and willingness to undergo screening (p = 0.016).ConclusionThis study revealed discordance between awareness and knowledge about cervical cancer. Educational initiatives reflective of population perception/knowledge of cervical cancer are needed to mitigate the rising incidence of this disease, especially among female healthcare providers

SPARC 2018 Internationalisation and collaboration : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2018 SPARC conference. This year we not only celebrate the work of our PGRs but also the launch of our Doctoral School, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 100 presenters, the conference truly showcases a vibrant PGR community at Salford. These abstracts provide a taster of the research strengths of their works, and provide delegates with a reference point for networking and initiating critical debate. With such wide-ranging topics being showcased, we encourage you to take up this great opportunity to engage with researchers working in different subject areas from your own. To meet global challenges, high impact research inevitably requires interdisciplinary collaboration. This is recognised by all major research funders. Therefore engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers

Few-Shot Network Intrusion Detection Using Discriminative Representation Learning with Supervised Autoencoder

Recently, intrusion detection methods based on supervised deep learning techniques (DL) have seen widespread adoption by the research community, as a result of advantages, such as the ability to learn useful feature representations from input data without excessive manual intervention. However, these techniques require large amounts of data to generalize well. Collecting a large-scale malicious sample is non-trivial, especially in the modern day with its constantly evolving landscape of cyber-threats. On the other hand, collecting a few-shot of malicious samples is more realistic in practical settings, as in cases such as zero-day attacks, where security agents are only able to intercept a limited number of such samples. Hence, intrusion detection methods based on few-shot learning is emerging as an alternative to conventional supervised learning approaches to simulate more realistic settings. Therefore, in this paper, we propose a novel method that leverages discriminative representation learning with a supervised autoencoder to achieve few-shot intrusion detection. Our approach is implemented in two stages: we first train a feature extractor model with known classes of malicious samples using a discriminative autoencoder, and then in the few-shot detection stage, we use the trained feature extractor model to fit a classifier with a few-shot examples of the novel attack class. We are able to achieve detection rates of 99.5% and 99.8% for both the CIC-IDS2017 and NSL-KDD datasets, respectively, using only 10 examples of an unseen attack

Few-Shot Network Intrusion Detection Using Discriminative Representation Learning with Supervised Autoencoder

Recently, intrusion detection methods based on supervised deep learning techniques (DL) have seen widespread adoption by the research community, as a result of advantages, such as the ability to learn useful feature representations from input data without excessive manual intervention. However, these techniques require large amounts of data to generalize well. Collecting a large-scale malicious sample is non-trivial, especially in the modern day with its constantly evolving landscape of cyber-threats. On the other hand, collecting a few-shot of malicious samples is more realistic in practical settings, as in cases such as zero-day attacks, where security agents are only able to intercept a limited number of such samples. Hence, intrusion detection methods based on few-shot learning is emerging as an alternative to conventional supervised learning approaches to simulate more realistic settings. Therefore, in this paper, we propose a novel method that leverages discriminative representation learning with a supervised autoencoder to achieve few-shot intrusion detection. Our approach is implemented in two stages: we first train a feature extractor model with known classes of malicious samples using a discriminative autoencoder, and then in the few-shot detection stage, we use the trained feature extractor model to fit a classifier with a few-shot examples of the novel attack class. We are able to achieve detection rates of 99.5% and 99.8% for both the CIC-IDS2017 and NSL-KDD datasets, respectively, using only 10 examples of an unseen attack

Unilateral sinonasal masses: Review of clinical presentation and outcome in Ahmadu Bello University Teaching Hospital, Zaria, Nigeria

Background: Unilateral persistent nasal obstruction may indicate the presence of sinonasal lesion, which could be inflammatory or neoplastic. It is a common practice to assume that unilateral nasal mass in adults is either inverted papilloma or a malignant lesion. Objectives: The objective is to study the pattern of clinical presentation and outcome of treatment of patients managed for unilateral nasal masses at Ahmadu Bello University Teaching Hospital, Zaria. Materials and Methods: The record of patients managed for unilateral nasal masses over 5 years between January 2013 and December 2017 was reviewed. Data obtained for this study included demographic characteristics such as age, sex, occupation, main presenting symptoms, duration of symptoms, histological type, type of treatment given, and current status of patients. The data were analyzed using the Statistical Package for the Social Science version 23.0. Results: A total of 38 cases were reviewed for this study and there were 25 (65.8%) males and 13 (34.2%) females with a sex ratio (male: female) of 1.9:1. The mean age was 50.8 years, with the standard deviation of ± 13.7. Rhinorrhea, nasal blockage and the presence of nasal growth were the most common symptoms at presentation seen nearly in all the patients. Inflammatory polyp 16 (42.1%) was the most common histological type observed in this study. The majority of patients with malignant sinonasal masses had well‑differentiated squamous cell carcinoma 5 (13.2%). Most of our patients 29 (76.3%) presented to the hospital within 1–3 years of the onset of the symptoms. The majority of our patients 26 (68.4%) did very well and were discharged from the clinic following resolution of their symptoms. Three (7.9%) had recurrent nasal mass. We recorded three cases of mortality from the 38 patients managed. Conclusion: Inflammatory polyp was the most common unilateral sinonasal mass followed by inverted papilloma. A thorough clinical evaluation of any patients with prolonged nasal symptoms will go a long way in the early detection of these lesions

Wind Power Generation in Sudano-Sahelian Region of Nigeria: a Review

Over a couple of years, the world's energy demand has turned to renewable energy sources due to the menace of global warming, while some African countries still depend on fossil fuels despite their harmful effects. Out of approximately 4 trillion (kWh) of renewable energy that is expected to be generated by the year 2030, wind energy is projected to contribute up to 1.1 trillion (kWh). Wind energy studies will be the centre for future renewable engineering efforts, being one of the most likely economic and affordable alternate energy sources. Furthermore, wind resources analysis has also revealed that the Northern part of Nigeria, which occupies almost all the meteorological locations in the Sudano-Sahelian Ecological Zone, possesses enormous potential for harvesting wind energy. This paper involves a systematic review of relevant literature to identify the outcome of various initiatives of researchers at appraising the prospects of electricity production from wind for sustainable development in the region. It was established that the area is blessed with enormous opportunities for harnessing wind for various applications, having possible average wind speeds reaching as high as 8.70 m/s at 10 m above the ground. The region can adequately utilize wind for power generation if the fundamental challenges facing wind energy utilization are addressed. There is a need to systematically model and simulate the system's feasibility before actual implementation to assist in other managerial and technical decisions. Wind energy integration will immensely contribute to providing lasting solutions to the energy situation in the region and the country at large

Time-Kill Kinetic Effect of Sodium Citrate, Sodium Nitrite and Cinnamaldehyde Against Biofilm Forming Escherichia coli O157:H7

Food safety is a significant concern of every sector of the food industry. Survival of Escherichia coli O157:H7 with biofilm-forming potential in commercial food premises is a possible danger to consumers’ health, especially in societies where most of the population depend on it for their daily meals. Preservation of fresh food quality being of utmost importance, new innovative means of inhibiting pathogenic microorganisms in foods are being evaluated to be effective at destroying microorganisms and preserving the physical and organoleptic properties. This study aimed to inhibit biofilm formation of Escherichia coli O157:H7 by food additives; sodium citrate, sodium nitrite and cinnamaldehyde. The isolate obtained was subjected to Gram’s staining and various biochemical identifications and later confirmed by the latex agglutination test. The Escherichia coli O157:H7 was further subjected to a biofilm formation potential test on Congo red media. Antimicrobial susceptibility testing was conducted to obtain the susceptibility/resistance pattern of the isolate to the food additives. The MIC, MBC and time-kill kinetics effect was determined following CLSI 2017 guideline. The highest growth inhibition zone of 31 mm was exhibited by cinnamaldehyde, followed by sodium nitrite with 26 mm and sodium citrate with 13 mm. The MIC was determined to be 2.5 mg/ml for sodium citrate, 0.25 mg/ml for sodium nitrite and 0.125 µl/ml for cinnamaldehyde. Sodium citrate was found to be bacteriostatic between 6-8 hrs with 72.9 % reduction, sodium nitrite and cinnamaldehyde exhibit both bacteriostatic and bactericidal effects between 2-24 hrs with percentage inhibition of 65-90 % and 63-100 %, respectively. This study showed that sodium citrate, sodium nitrite and cinnamaldehyde exerted strong antimicrobial properties indicating their potential as suitable preservatives