Miracle-dz/UniFAR-FTUs huggingface dataset:
Uptake of Open Distance and e-Learning (ODEL) programmes: A Case of Kenyatta University, Kenya

Demand for higher education in Kenya has continued to rise over the years thereby outstripping the available supply in the conventional face-to-face programmes. This can be attributed to two major factors. First, are the reforms in the basic education sector, for example, the Free Primary Education and the Free Day Secondary Education which have enhanced enrolment and completion rates in these lower levels. Second, is the changing labour market trend which requires workers to be re-tooled during their working life. Universities therefore have to cope with demand for education from young secondary school graduates as well as older citizens who are already working. To meet this high demand for higher education as well as provide flexible education for the working class, universities in Kenya must leverage the potential of ICT in teaching and learning. Despite moves by most universities in Kenya more than a decade ago to embrace Open and distance learning (ODL) programmes that utilise modern ICT technologies in teaching and learning, enrolment in these programmes still remain low compared to the traditional face-to-face platform of delivery. For example, in 2016, Kenyatta University, which had a total student population of about 70,000 had only about 6,000 (8.5%) enrolled in the Digital School of Virtual and Open Learning. The objective of this study is to establish the obstacles that hinder the success of Open and Distance Learning programmes at Kenyatta University. The study employed a sequential mixed methods design that allowed collection of both quantitative and qualitative data. Data was collected from a sample of 207 students through a questionnaire while Key Informant Interviews were conducted with 5 members of staff directly involved either in the management of the ODeL programme or in on-line teaching. The study established that success of the ODeL programme was hampered by technical, instructional, institutional and personal challenges. Key technical challenges faced by both students and staff are insufficient exposure to computers and ICT technology, lack of finances to buy ICT gadgets and lack of internet connectivity. Key institutional challenges facing the programme are delayed delivery of study materials and inadequate learner support services. With regard to instructional challenges, inadequate academic support due to lecturers failing to facilitate units on-line and poorly designed course materials were the key ones. Lastly, learners in the programme faced individual challenges such as financial constraints, insufficient study time, conflict between study and family/work balance. The study recommends the strengthening of learner support mechanisms to address the institutional, instructional and individual challenges faced by learners in the ODeL programme. Keywords: Blended learning, distance learning, e-learning, higher education, ICT, ODel, open learning.
Forecasting Football Match Results in National League Competitions Using Score-Driven Time Series Models

We develop a new dynamic multivariate model for the analysis and forecasting of football match results in national league competitions. The proposed dynamic model is based on the score of the predictive observation mass function for a high-dimensional panel of weekly match results. Our main interest is in forecasting whether the match result is a win, a loss or a draw for each team. The dynamic model for delivering such forecasts can be based on three different dependent variables: the pairwise count of the number of goals, the difference between the numbers of goals, or the category of the match result (win, loss, draw). The different dependent variables require different distributional assumptions. Furthermore, different dynamic model specifications can be considered for generating the forecasts. We investigate empirically which dependent variable and which dynamic model specification yield the best forecasting results. We validate the precision of the resulting forecasts and the success of the forecasts in a betting simulation in an extensive forecasting study for match results from six large European football competitions. Finally, we conclude that the dynamic model for pairwise counts delivers the most precise forecasts while the dynamic model for the difference between counts is most successful for betting, but that both outperform benchmark and other competing models.
Corporate social disclosure under isomorphic pressures: evidence from business groups

This paper investigates the relationship between ownership and corporate social disclosure (CSD) with the aim of answering the following research questions: Can the affiliation of listed companies in a wider business group influence their CSD? Do the affiliated listed companies have CSDs similar to each other and/or to their parent company? If the businesses of affiliated listed subsidiaries are unrelated, how much of their CSD can be explained by the industry in which they operate instead of their group affiliation? The multiple case studies analysis developed through a content analysis applied to 13 business groups reveal whether and how the affiliation is influential on CSD. Findings show that the CSD of an entity is strongly affected by affiliation to a business group, both when subsidiaries operate in the same industry as their parent and when, notwithstanding the unrelated business, the directional activity of the parent is particularly significant.
AN ITERATIVE TERRAIN RECOVERY APPROACH TO AUTOMATED DTM GENERATION FROM AIRBORNE LIDAR POINT CLOUDS

This paper presents a hierarchical recovery method to generate DTMs from airborne LiDAR point clouds based one an idea of layering. The developed method first registers the last return points, and then layering them. The layering is done by dividing the points into different height layers and assigning layer numbers to each point. The layer numbers are comparing references in later identification process. Then a series of rasterized pyramid levels which consisted of lowest points are generated. Since the outliers have been removed after the layering, the cells in top level are considered to be terrain points and used as reference to identify cells in the following level. After the identification of the second level, an interpolation will occur in the cells which identified as offterrain. And the interpolated level will be used as reference in its following level and the same process is repeated at each level. Once this process of the bottom level finished, the proposed method adjusts the results based on the first return feedback and followed by the final interpolation. As a result, this produces the final DTM. The developed method is data driven, and does not assume a prior knowledge about the scene complexity. The proposed method was tested with the ISPRS WG III/3 LiDAR datasets covering different terrain types and filtering difficulties. The results show that the proposed method can perform well in flat terrain or gentle slope area.
Consumer Preferences for Japanese Quince ( Chaenomeles japonica ) Products

A study of consumer preferences in Sweden showed that the consumers in general responded very positively to the flavour of Japanese quince in various products. Of the products tested, chaenomeles ice cream was the product liked by most consumers, and on average 80% of the consumers questioned would buy the ice cream if it were available on the market. Chaenomeles lemonade and chaenomeles curd were also very much appreciated. Curd-type preservatives seemed to be unknown for many of the Swedish consumers surveyed. Nevertheless, chaenomeles curd obtained high scores and 83% of women aged 40– 60 would buy the product if available on the market. Less appreciated (however with high scores) were jam and yoghurt with the highest buying preferences for 75% for women aged 40–60 and 62% for women aged 20–39. These products could be further developed and thereby appreciated by more consumers.
1 Expression pattern of miR-146 a in experimental and human temporal lobe epilepsy

Increasing evidence supports the involvement of inflammatory and immune processes in temporal lobe epilepsy (TLE). MicroRNAs (miRNA) represent small regulatory RNA molecules that have been shown to act as negative regulators of gene expression controlling different biological processes, including immune-system homeostasis and function. We investigated the expression and cellular distribution of miRNA-146a (miR-146a) in a rat model of TLE as well as in human TLE. miR-146a analysis in rat hippocampus was performed by polymerase chain reaction and immunocytochemistry at 1 week and 3–4 months after induction of status epilepticus (SE). Prominent upregulation of miR-146a activation was evident at 1 week after SE and persisted in the chronic phase. The miR-146a expression was confirmed to be present in reactive astrocytes. In human TLE with hippocampal sclerosis, increased astroglial expression of miR-146a was observed mainly in regions where neuronal cell loss and reactive gliosis occurred. The increased and persistent expression of miR-146a in reactive astrocytes supports the possible involvement of miRNAs in the modulation of the astroglial inflammatory response occurring in TLE and provides a target for future studies aimed at developing strategies against pro-epileptogenic inflammatory signalling.
Understanding the economic impact terrorism has on the destination decision making : Northern Irish tourists

The aim of this study is to understand perceptions of Irish tourist with respect to tourist destinations that have faced a terrorist attack in recent years. This study focuses on Paris where terrorism incidents occurred and aims to understand how these attacks affect tourists‟ perception in Ireland. There is a need to conduct studies in relation to impact of terrorism on tourism as tourism is considered to be one of the important sources of economic activities and income for individuals and economies in modern world. Although there is significant amount of literature focusing on impact of terrorism, however, majority of the studies lack a perspect ive from tourists. Although it is important to study economic impacts of terrorism using economic indicators, yet it is also important to understand how individual tourists are affected by such incidents. This study conducted a focus group consisting of six participants. Data collection method was a questionnaire that contained closed ended and open ended questions. The results of the study indicate that terrorism has a significant impact on tourists‟ choice of destination. Within the context of Paris, terrorist attacks in Brussels have affected Paris‟ brand as a tourism destination. This study also found that media coverage, particularly negative media coverage also have significant impact on tourists decision making process. Within the context of Paris this study found that perception of risk increases due to terrorist‟s attacks however, general perception of risk is typically higher than actual risks. Tourists develop a positive opinion about terrorist affected area and majority of the tourist feel safe in Paris despite terrorist attacks. This study recommends that marketing and branding campaigns are critical for Paris to recover its position as a safe and attractive tourist destination in the world. Terrorism and Tourism 5
The impact of price change on consumer choice of automobiles

The objective of this paper is to examine whether a change in the price of a given model of national automobiles affects the choice of alternative car models by consumers. Four models of national automobiles - Saga 1.3cc, Saga 1.5cc, Wira 1.3cc, and Wira 1.5cc - are considered over the period 2000–2002. The results based on the conditional logit model indicate that all of the alternative models are substitutes to each other.
A FORTRAN Code for the Sensitivity Estimate of a Seismic Network: An Application to Campi Flegrei

The resolution power of a seismic network is a crucial point both for scientific and legal reasons. Firstly it allow to understand whether an area is not affected by seismicity or we are just not able to detect it; consequently it is an important parameter when the possible seismicity is eventually associated with human activities. When subsoil exploitation is planned a certain minimum level of sensitivity to earthquake location is indeed usually required for the monitoring network to be installed. The sensitivity of a seismic network is its ability to detect or locate earthquakes. Here we present free downloadable and friendly software to define the sensitivity of a seismic network. Input to the program are the station positions, the seismic noise level of the area and the mean elastic properties of the area and the output is a grid with the minimum magnitude of earthquakes which are localizable or detectable at a certain depth.
Optimum-time, Optimum-space, Algorithms for k-mer Analysis of Whole Genome Sequences

The sizable amount of data generated by high throughput cell biology is increasing the demand on traditional computational tools in bioinformatics to handle large input datasets. Large sequence data sets create intractable search spaces that are beyond the scope of many conventional algorithms. One way to address this problem is to transform large sequence data sets to the constituent parts that characterize the features of interest (e.g. transcription factor binding sites, miRNA sites, etc.) of the problem. These features of interest take the form of k-mers in a large subset of problems in computational biology. K-mers also play an implicit role in many other bioinformatics functions from microarray probes to genomic compositional analysis.Given the increasing potential for k-mers in a wide spectrum of applications in bioinformatics we present in this paper a set of fast and efficient generic algorithms for enumerating the occurrence frequen-cies of all substrings of a given length (kmers) in whole genome sequences. Described are three algorithms of increasing complexity designed to deal with different k-mer lengths from short (couple of bases) to very long (tens of thousands of bases). They are memory based algorithms that use advanced heuristics to efficiently process large amounts of data that arise when analyzing very long genome sequences. The algorithms were tested for performance on the human, mouse, 681 bacteria and 50 archaea genome sequences. Results are described for both time and space utilization. We also describe several different experiments that demonstrate the utility of these algorithms. These algorithms can be downloaded from http://www2.kumc. edu/siddrc/bioinformatics/publication. html.
Determinants Of Cost Efficiency In Malaysian Banking

This study estimates the cost efficiency and its decompositions of Malaysian banks over the period of 1995 to 2010 by utilising data envelopment analysis (DEA) method. Instead of estimating efficiency based on DEA separate frontiers approach; this study departs from practice of many previous studies by pooling the data set to build a DEA common frontier. This study contributes to the existing literature by integrating determinants of banking efficiency into the areas of DEA methodology in the context of Malaysian banking system across individual domestic banks. The first objective of this study is to estimate cost efficiency and its decompositions, which are technical and allocative efficiency as well as to estimate sources of technical efficiency namely pure technical efficiency and scale efficiency. Next, Tobit regression analysis is undertaken to identify the determinants of various measures of banking efficiency. The results indicate that government ownership, population density, demand density and market concentration are positively associated with several measures of efficiency while year that merger takes place, macroeconomic condition, capitalization, credit risk, asset quality and management quality have a negative relationship with various measures of efficiency. However, the size of banks is found to have mixed sign, positive coefficient with technical and pure technical efficiency while the negative relationship with scale efficiency, cost and allocative efficiency.
The Changing Way Governments Talk About Poverty and Inequality: Evidence from Two Centuries of Latin American Presidential Speeches

This study uses text mining techniques on almost 900 presidential ‘state-of-the-union’, type speeches from 10 Latin American countries from 1819 to 2016. The paper documents a sharp increase in recent decades in references to poverty and inequality. The study’s long-term view shows that the way in which poverty and inequality are discussed has been changing. Using a Latent Dirichlet Allocation algorithm, the paper shows that in recent years poverty has been increasingly discussed as a broader multidimensional challenge that requires a variety of social programs. Inequality has been increasingly framed as an issue of equal opportunities, whereas previously there was a greater focus on social justice. The paper assesses whether the prevalence of poverty and inequality in presidential speeches correlates with measures such as social public spending, as well as the poverty and inequality levels of the country. It finds that during the 2000s, the countries that discussed poverty and inequality at greater length were also the ones that increased social spending and educed poverty and inequality the most.
Electrochemical Behaviour of Thymolphthalein

The polarographic and voltammetric behaviour of thymolphthalein in ethanol-water (1/5 v/v) was studied using various electrochemical techniques. The reduction of thymolphthalein on a mercury drop electrode was investigated. The adsorption effect on the electrode surface was observed. The rate constants for the electron transfer steps were determined by and without taking adsorption into occount using the Laviron technique and Nicholson technique respectively. The diffusion coefficients were calculated from the cyclic voltammetric data using the method developed by Garrido. Reversibility for the electrode reaction was investigated and a mechanism for the electrode reaction was proposed.
A New Kernel Orthogonal Projection Analysis Approach for Face Recognition

In the field of face recognition, how to extract effective nonlinear discriminative features is an important research topic. In this paper, we propose a new kernel orthogonal projection analysis approach. We obtain the optimal nonlinear projective vector which can differentiate one class and its adjacent classes, by using the Fisher criterion and constructing the specific between-class and within-class scatter matrices in kernel space. In addition, to eliminate the redundancy among projective vectors, our approach makes every projective vector satisfy locally orthogonal constraints by using the corresponding class and part of its most adjacent classes. Experimental results on the public AR and CAS-PEAL face databases demonstrate that the proposed approach outperforms several representative nonlinear projection analysis methods.
Dynamic linkages among European carbon markets

A number of studies have tested for cointegration between spot and futures prices in the European carbon markets. These studies tend to focus on the price discovery role of futures versus spot prices. In this paper, we draw the attention to the short- and long-run dynamic linkages among distinct European carbon markets by investigating the interdependence and the transmission efficiency between European Climate Exchange (ECX), Nordic Power Exchange (NordPool) and European Energy Exchange (EEX). To this end, we test for cointegration between European Union carbon allowances (EUAs) futures prices and also, we conduct causality tests to examine spillover dynamics. Our findings indicate that the markets exhibit a reasonable degree of efficiency in both short- and long-run.
Proton Magnetic Resonance Spectroscopy H MRS) in Schizophrenia: Investigation of the Right and Left Hippocampus, Thalamus, and Prefrontal Cortex

Single voxel proton magnetic resonance spectroscopy ('H MRS) was used to study the metabolites N-acetyl-aspartate (NAA), choline (CHO), and myo-inositol (ml) in order to test a neurodegenerative hypothesis in schizophrenia (decrease of NAA, increase of CHO, and increase of ml) and a cerebral asymmetry of these metabolites. 1 H MRS was performed in 17 schizophrenia patients and 14 healthy subjects in three cerebral areas highly involved in the pathophysiology of schizophrenia (the prefrontal cortex, the thalamus, and the hippocampus). The ratio amplitudes between metabolites and creatine plus phosphocreatine (Cr) were determined. No difference in the metabolites existed between patients and healthy subjects. However, relationships were noted between NAA/Cr and age in the thalami of the schizophrenia patients (r = -0.37; p = 0.14) and healthy subjects (r = -0.52; p = 0.05). A significant correlation was observed between NAA/Cr and age of onset of illness in the hippocampi of schizophrenia patients (r = -0.59; p < 0.05). Moreover, NAA/Cr was lower in the right than in the left prefrontal cortex in both schizophrenia patients and healthy subjects. There was no relationship between the metabolites and duration of illness or dose of antipsychotics. These findings might suggest a neurodegenerative process in the hippocampi of schizophrenia patients with late onset of illness, and the NAA/Cr ratio could be a marker of aging in the thai-ami.
Chapter 5 Exercise Therapy for Physical Therapist

This chapter describes exercise therapy in terms of definition, objectives, concept, techniques, mechanisms, and equipment. Mechanisms explaining the effect of exercise training on treatments for other diseases are included. In addition, new biomarkers capable of evaluating exercise performance capacity and progress in training and early detection of overtraining are provided. Very promising are mainly small non‐coding microRNAs (miRNAs). Important background knowledge for exercise therapy is also provided. The knowledge covers the exercise for healthy and unhealthy people. The former includes sedentary and sport player. The latter includes patients with various diseases, for example, metabolic diseases, cardiovascular disease, orthopedics, etc. Importantly, all the knowledge was presented in latest information.
Sustaining business networks: Understanding the benefit bundles sought by members of local business associations

Local business associations can be important mechanisms for stimulating inter-firm cooperation leading to economic growth and development. However, previous research suggests that the unfulfilled expectations of their members can lead to low participation, high membership churn and network instability over time. As a departure from studies that have explored why local associations supply certain benefits and services, this paper draws on an original, demand side membership survey of local business associations to identify for the first time the bundles of benefits sought by members. Two bundles of benefits (instrumental and info-social) relating to thin and thick models of rational choice, respectively, are identified in explaining why firms join and remain part of associations. The relevance of these bundles to members was found to vary with business profile and length of membership, with the value of instrumental benefits reducing over time, whereas the demand for info-social benefits remained relatively stable. The findings have important implications for local strategies for sustaining business networks.