Morphological Doubling theory to two Bantu Languages Reduplication: A comparative perspective of Kinyarwanda and Swahili

Reduplication is a morphological phenomenon which has attracted attention of many researchers in various fields of Linguistics using a number of theories for many languages of the globe. Among other African languages, Kinyarwanda and Swahili have been studied under various approaches each but few comparative studies were conducted on these two Bantu languages spoken in Rwanda and its neighbouring countries of East African region. The aim of this study is to have a look into reduplication- a word formation process, with specific focus on Kinyarwanda and Swahili. Basing on Morphology Doubling Theory (MDT), the researchers examined the similarities and differences between the two languages. Both bounded and unbounded reduplication- full and partial word levels were concerned. Descriptive analysis revealed that the two members of the same set inherently share reduplication features basically complete root, partial and/or syllabic repetition in word formation process

Conspecific and allospecific larval extracts entice mosquitoes to lay eggs and may be used in attract-and-kill control strategy.

One of the strategies of integrated vector management is to lure gravid mosquitoes for surveillance purposes or to entice them to lay eggs in water containing toxins that kill the offspring (attract-and-kill or trap-and-kill). Typically, the major challenge of this approach is the development of a lure that stimulates oviposition plus a toxin with no deterrent effect. Bacillus thuringiensis var. israelensis (Bti) satisfies the latter criterion, but lures for these autocidal gravid traps are sorely needed. We observed that gravid Aedes aegypti, Ae. albopictus, and Culex quinquefasciatus laid significantly more eggs in cups with extracts from 4th-stage larvae (4 L) of the same or different species. No activity was found when 4 L were extracted with hexane, diethyl ether, methanol, or butanol, but activity was observed with dimethyl sulfoxide extracts. Larval extracts contained both oviposition stimulant(s)/attractant(s) and deterrent(s), which partitioned in the water and hexane phases, respectively. Lyophilized larval extracts were active after a month, but activity was reduced by keeping the sample at 4 °C. In the tested range of 0.1 to 1 larvae-equivalent per milliliter, oviposition activity increased in a dose-dependent manner. In field experiments, Ae. aegpti laid significantly more eggs in traps loaded with larval extracts plus Bti than in control traps with water plus Bti

Predictors of walking capacity in peripheral arterial disease patients

OBJECTIVE: To estimate walking capacity in intermittent claudication patients through a prediction model based on clinical characteristics and the walking impairment questionnaire. METHODS: The sample included 133 intermittent claudication patients of both genders aged between 30 and 80 years. Data regarding clinical characteristics, the walking impairment questionnaire and treadmill walking test performance were obtained. Multiple regression modeling was conducted to predict claudication onset distance and total walking distance using clinical characteristics (age, height, mass, body mass index, ankle brachial index lower, gender, history of smoking and co-morbid conditions) and walking impairment questionnaire responses. Comparisons of claudication onset distance and total walking distance measured during treadmill tests and estimated by a regression equation were performed using paired t-tests. RESULTS: Co-morbid conditions (diabetes and coronary artery disease) and questions related to difficulty in walking short distances (walking indoors - such as around your house and walking 5 blocks) and at low speed (walking 1 block at average speed - usual pace) resulted in the development of new prediction models high significant for claudication onset distance and total walking distance (p0.05) were observed. CONCLUSION: The current study demonstrated that walking capacity can be adequately estimated based on co-morbid conditions and responses to the walking impairment questionnaire

INTERROGATING THE CONTRIBUTIONS OF ICT ACQUISITION AND APPLICATION TO EFFECTIVE LIBRARY SERVICE DELIVERY IN NIGERIA

It is a fact that acquisition and application of Information and Communication Technology (ICT) contribute positively to effectiveness of academic libraries’ delivery of information services. The extent to which this is the case in Nigeria was interrogated in this study in order to justify the huge investment in ICT. Survey research design was adopted. The study population comprises professional librarians in academic libraries in Nigerian universities. The instrument used for data collection was the questionnaire complemented with interviews. A Total of 150 copies of the questionnaire were administered out of which 120 copies were retrieved giving 80.0% response rate. Analysis of the data collected was done using descriptive statistics in form of frequency counts, percentages and tables. Results shown that it librarians are aware of ICT tools and the benefits of using them. Irrespective of this none of the academic libraries in Nigerian universities have been able to maximized the benefits as due to the plethora of limiting factors such as internal politics (100%), epileptic power supply (100%) and lack of skilled systems analysts/engineers (91.7%) and inadequate funding (83.3%). Also revealed as a critical inhibitor to ICT acquisition and application in academic libraries is poor predisposition of the university librarians ICT projects as strongly agreed to by 85 (70.8%) respondents. The study however concluded on the note that ICT acquisition and application in academic libraries have the potential to offer innumerable benefits to the professionalization of librarianship in Nigeria through enhanced library operations and the provision of information services to library users

Citation analysis of most prolific authors in the field of Library and Information Science in Nigeria

The aim of the study is to carry out a citation analysis of ten most prolific academic scholars in the field of Library and Information Science (LIS) in Nigeria and also determine their authorship pattern. Google scholar database was used in searching for articles published from 2000 to May, 2018. Ten academic researchers in the field of LIS in Nigeria were studied. Results from the analysis show that, Tella, Adeyinka with 72 articles had a total of 1,740 citations and is the most cited author among the ten most prolific authors in the field of Library and Information Science in Nigeria, followed by Adomi, E. Esharenana with 904 citations from 47 articles, and Nwagwu, E. Williams with 684 citations from 70 articles. The authorship patterns of the publications revealed that majority of the articles were co-authored papers. Further analysis showed that the degree of collaboration among the researchers was high. The correlation of the most cited articles with most cited journals revealed the Library Philosophy & Practice as the most cited journal. The study calls for authorities in institutions and editors of local journals to find solutions to the inclusion of local journals in international indexing and abstraction databases to present a realistic picture of scholarly publications

The Z Curve:

The demand for a Giffen good is atypical, i.e. it increases as prices rise. The traditional representation for this phenomenon is a simple upward sloping demand curve. This model is very problematic, because it implies that demand can oscillate between infinity and negative infinity, an unrealistic scenario to say the least. In this paper we briefly discuss the problems with the traditional model and propose a better one: the Z curve. Because Giffen goods are a consequence of a reduction in the consumer’s income, the Z curve illustrates the effects of this change on wealth. Our goal here is not to dismiss the mental construction of Giffen Goods entirely . Rather, we bring forth what we believe to be a more precise method to graphically represent Giffen Goods

Learning Interpretable Rules for Multi-label Classification

Multi-label classification (MLC) is a supervised learning problem in which, contrary to standard multiclass classification, an instance can be associated with several class labels simultaneously. In this chapter, we advocate a rule-based approach to multi-label classification. Rule learning algorithms are often employed when one is not only interested in accurate predictions, but also requires an interpretable theory that can be understood, analyzed, and qualitatively evaluated by domain experts. Ideally, by revealing patterns and regularities contained in the data, a rule-based theory yields new insights in the application domain. Recently, several authors have started to investigate how rule-based models can be used for modeling multi-label data. Discussing this task in detail, we highlight some of the problems that make rule learning considerably more challenging for MLC than for conventional classification. While mainly focusing on our own previous work, we also provide a short overview of related work in this area.Comment: Preprint version. To appear in: Explainable and Interpretable Models in Computer Vision and Machine Learning. The Springer Series on Challenges in Machine Learning. Springer (2018). See http://www.ke.tu-darmstadt.de/bibtex/publications/show/3077 for further informatio

Mapping the disease-specific LupusQoL to the SF-6D

Purpose To derive a mapping algorithm to predict SF-6D utility scores from the non-preference-based LupusQoL and test the performance of the developed algorithm on a separate independent validation data set. Method LupusQoL and SF-6D data were collected from 320 patients with systemic lupus erythematosus (SLE) attending routine rheumatology outpatient appointments at seven centres in the UK. Ordinary least squares (OLS) regression was used to estimate models of increasing complexity in order to predict individuals’ SF-6D utility scores from their responses to the LupusQoL questionnaire. Model performance was judged on predictive ability through the size and pattern of prediction errors generated. The performance of the selected model was externally validated on an independent data set containing 113 female SLE patients who had again completed both the LupusQoL and SF-36 questionnaires. Results Four of the eight LupusQoL domains (physical health, pain, emotional health, and fatigue) were selected as dependent variables in the final model. Overall model fit was good, with R2 0.7219, MAE 0.0557, and RMSE 0.0706 when applied to the estimation data set, and R2 0.7431, MAE 0.0528, and RMSE 0.0663 when applied to the validation sample. Conclusion This study provides a method by which health state utility values can be estimated from patient responses to the non-preference-based LupusQoL, generalisable beyond the data set upon which it was estimated. Despite concerns over the use of OLS to develop mapping algorithms, we find this method to be suitable in this case due to the normality of the SF-6D data