An hp-version discontinuous Galerkin method for integro-differential equations of parabolic type

We study the numerical solution of a class of parabolic integro-differential equations with weakly singular kernels. We use an $hp$-version discontinuous Galerkin (DG) method for the discretization in time. We derive optimal $hp$-version error estimates and show that exponential rates of convergence can be achieved for solutions with singular (temporal) behavior near $t=0$ caused by the weakly singular kernel. Moreover, we prove that by using nonuniformly refined time steps, optimal algebraic convergence rates can be achieved for the $h$-version DG method. We then combine the DG time-stepping method with a standard finite element discretization in space, and present an optimal error analysis of the resulting fully discrete scheme. Our theoretical results are numerically validated in a series of test problems

TILLAGE SYSTEMS FOR MINNESOTA FARMS: ALTERNATIVE TECHNOLOGIES, ECONOMIC CONSIDERATIONS, AND DATA NEEDS

Crop Production/Industries,

A Review of TV White Space Technology and its Deployments in Africa

The emergence of bandwidth-driven applications in the current wireless communication environment is driving a paradigm shift from the conventional fixed spectrum assignment policy to intelligent and dynamic spectrum access. Practical demands for efficient spectrum utilization have continued to drive the development of TV white space technology to provide affordable and reliable wireless connectivity. It is envisaged that transition from analogue transmission to Digital Terrestrial Television (DTT) creates more spectrum opportunity for TV white space access and regulatory agencies of many countries had begun to explore this opportunity to address spectrum scarcity. To convey the evolutionary trends in the development of TV white space technology, this paper presents a comprehensive review on the contemporary approaches to TV white space technology and practical deployments of pilot projects in Africa. The paper outlines the activities in TV white space technology, which include regulations and standardization, commercial trials, research challenges, open issues and future research directions. Furthermore, it also provides an overview of the current industrial trends in TV white space technology which demonstrates that cognitive radio as an enabling technology for TV white space technology

Contribution of beta1- and beta2-adrenergic receptors to cochlear function

Sympathetic innervation is heavily present in the cochlea. However, its role in the development and maintenance of normal hearing remains debatable. Beta1-adrenergic receptors 1 (beta1-ARs) and beta2-adrenergic receptors (beta2-ARs) are two types of receptors that are stimulated by the sympathetic nervous system and are expressed by many cochlear cell types. In this study, we have analyzed the functional consequences of the lack of beta-ARs in the cochlea. We have first evaluated hearing thresholds using auditory brainstem response and distortion product otoacoustic emissions in young and aged knockout mice lacking beta1-ARs, beta2-ARs, or both beta1-ARs and beta2-ARs. Secondly, we tested the sensitivity of these mice to acoustic overexposure. Hearing tests revealed similar normal thresholds in all beta- adrenergic receptors mice when compared to age matched wild type controls. When exposed to noise mice lacking beta1- but not beta2- AR exhibited a subtle protection of hearing thresholds at the low frequencies only. These results suggest that despite being expressed by many cochlear cell types these beta-ARs are not playing a crucial role in hearing development and maintenance

Appraisal of environmental sustainability studies in the quantity surveying curriculum

The construction industry requires professionals that are environmentally sensitive to sustain the built environment for future generation. This is necessary due to the rising environmental degradation from various construction activities. Tertiary institutions could be the appropriate platform to instil these ideas in aspiring construction professionals. This study assessed Quantity Surveying (QS) curriculum of Polytechnics to examine the courses taught and to assess whether there are courses in the curriculum that are related to environmental sustainability studies. Also, questionnaires administered to lecturers and students of QS departments was used to examine the concept and awareness of environmental sustainability taught in the institution. The study established that generally, taught courses in QS departments of Polytechnics have little or no environmental sustainability factored into them. Furthermore, cumulative mean and regression analysis were used to evaluate the data obtained from the questionnaire. The analysis established that the respondents affirmed that the QS curriculum does not create awareness of environmental sustainability, having a cumulative mean score of 2.04 for lecturers and 2.28 for students which is within the cut-off point of 1.5 to 2.5 (Disagree). Based on the regression analysis, it was established that the correlation between the lecturers’ and the students’ responses was significant having a R result of 0.95. The regression analysis explicated that the lecturers can explain the students’ views having a R2 value of 0.90. The review of QS curriculum to include environmental sustainability studies is paramount in producing QS professionals that are environmentally inclined in training. Keywords: Environmental Sustainability, Quantity surveying, Higher institutions and Curriculu

Analysing Knowledge-Sharing Practices Using Activity Theory in the SME Organisation

An activity theory method is used to analyse the knowledge-sharing practices. The activity theory emphasises the necessity of analysing the SME organisation as a whole. In the context of knowledge-sharing practices, activity theory is used to collect interconnected parts of SME practices. A cross-sectional design was used to study the relationship among relationship commitment, knowledge-sharing practices, employee development, team performance, and a moderating role of social identification. The majority of the SMEs were established 3–5 years ago (46.3%), and 84.4% were private, with an employee range of less than 50 (73.1%). Furthermore, 82.1% of the SMEs in this study were in the growth stage. Knowledge-sharing practices have a significant positive effect on team performance (0.278, [Formula: see text]), with a moderating impact of role and behaviour on knowledge-sharing practices and team performance (0.178, [Formula: see text]). The findings have confirmed the significant and positive effects of knowledge-sharing practices on the mediation of employee development (0.045, [Formula: see text]). The activity theory models for knowledge-sharing practices emphasise the contextual nature of knowledge sharing and ensure systematic evaluation

Transhydrogenation of pentane and 1-hexyne over CrOx/Al2O3 and potassium-doped CrOx/Al2O3 catalysts

The transhydrogenation of pentane (P) and 1-hexyne (1HY) was investigated over 4% CrOx/Al2O3 and potassium-doped 4% CrOx/Al2O3 catalysts over a range of temperatures (523–773 K) with a 5:1 P:1HY ratio. Over the CrOx/Al2O3 catalyst, transhydrogenation clearly occurred at temperatures below 625 K where the yield of alkenes was higher for the co-fed system than for a combination of the individual yields. Due to the acidic nature of the alumina, many of the products were alkylated olefins and alkylated hydrocarbons formed by coincident alkylation and isomerisation. When pentane was added to a feed containing 1-hexyne, the extent of carbon deposition was reduced. By comparing transhydrogenation to limited hydrogen 1-hexyne hydrogenation at 623 K, it was shown that the processes of hydrogenation and transhydrogenation were different, with hydrogenation favouring alkanes, while transhydrogenation favoured alkenes. This may be because pentane dehydrogenation only releases two hydrogen atoms, which only allows 1-hexyne to hydrogenate to 1-hexene. Therefore, if the rate of alkene isomerisation and desorption is faster than that of pentane dehydrogenation, only alkenes will be observed. The latter proposal would suggest that the dehydrogenation/hydrogenation process is closely coupled and would be consistent with pentane influencing 1-hexyne surface chemistry. The effect of the potassium doping was to increase the yield of alkenes. The reason for this may be related to changes in the nature of the surface chromia species. The potassium also neutralised the acid sites on the alumina, reducing the extent of alkylation and hydrogenolysis, which suppressed the formation of other alkynes in the product mix

Predictive Analysis of Students’ Learning Performance Using Data Mining Techniques: A Comparative Study of Feature Selection Methods

The utilization of data mining techniques for the prompt prediction of academic success has gained significant importance in the current era. There is an increasing interest in utilizing these methodologies to forecast the academic performance of students, thereby facilitating educators to intervene and furnish suitable assistance when required. The purpose of this study was to determine the optimal methods for feature engineering and selection in the context of regression and classification tasks. This study compared the Boruta algorithm and Lasso regression for regression, and Recursive Feature Elimination (RFE) and Random Forest Importance (RFI) for classification. According to the findings, Gradient Boost for the regression part of this study had the least Mean Absolute Error (MAE) and Root-Mean-Square Error (RMSE) of 12.93 and 18.28, respectively, in the case of the Boruta selection method. In contrast, RFI was found to be the superior classification method, yielding an accuracy rate of 78% in the classification part. This research emphasized the significance of employing appropriate feature engineering and selection methodologies to enhance the efficacy of machine learning algorithms. Using a diverse set of machine learning techniques, this study analyzed the OULA dataset, focusing on both feature engineering and selection. Our approach was to systematically compare the performance of different models, leading to insights about the most effective strategies for predicting student success