1,526 research outputs found
How to pave the way for greater energy cooperation in the GCC
Energy cooperation among member states of the GCC states could pave the way for further integration to increase economic efficiency, harmonise policies, improve governance and ensure security of supply. The region is facing a rapid increase in domestic energy demand as economic growth, coupled with large infrastructure and industrial projects, as well as population growth and immigration (total population jumped from 23 million in 1990 to 53 million in 2015), drive up electricity and fuel consumption. Additionally, such cooperation would create an even stronger regional bloc in the global oil market (that currently exists, to some extent, through OPEC)
Development and application of quantitative image analysis for preclinical MRI research
The aim of this thesis is to develop quantitative analysis methods to validate MRI and improve the detection of tumour infiltration. The major components include a description of the development the quantitative methods to better validate imaging biomarkers and detect of infiltration of tumour cells into normal tissue, which were then applied to a mouse model of glioblastoma invasion. To do this, a new histology model, called Stacked In-plane Histology (SIH), was developed to allow a quantitative analysis of MRI.
Validating imaging biomarkers for glioblastoma infiltration
Cancer can be defined as a disease in which a group of abnormal cells grow uncontrollably, often with fatal outcomes. According to (Cancer research UK, 2019), there are more than 363,000 new cancer cases in the UK every year, an increase from the 990 cases reported daily in 2014-2016, with only half of all patients recovering.
Glioblastoma (GB) is the most frequent and malignant form of primary brain tumours with a very poor prognosis. Even with the development of modern diagnostic strategies and new therapies, the five-year survival rate is just 5%, with the median survival time only 14 months.
Unfortunately, glioblastoma can affect patients at any age, including young children, but has a peak occurrence between the ages of 65 and 75 years. The standard treatment for GB consists of surgical resection, followed by radiotherapy and chemotherapy. However, the infiltration of GB cells into healthy adjacent brain tissue is a major obstacle for successful treatment, making complete removal of a tumour by surgery a difficult task, with the potential for tumour recurrence.
Magnetic Resonance Imaging (MRI) is a non-invasive, multipurpose imaging tool used for the diagnosis and monitoring of cancerous tumours. It can provide morphological, physiological, and metabolic information about the tumour. Currently, MRI is the standard diagnostic tool for GB before the pathological examination of tissue from surgical resection or biopsy specimens. The standard MRI sequences used for diagnosis of GB include T2-Weighted (T2W), T1-Weighted (T1W), Fluid-Attenuated Inversion Recovery (FLAIR), and Contrast Enhance T1 gadolinium (CE-T1) scans. These conventional scans are used to localize the tumour, in addition to associated oedema and necrosis. Although these scans can identify the bulk of the tumour, it is known that they do not detect regions infiltrated by GB cells.
The MRI signal depends upon many physical parameters including water content, local structure, tumbling rates, diffusion, and hypoxia (Dominietto, 2014). There has been considerable interest in identifying whether such biologically indirect image contrasts can be used as non-invasive imaging biomarkers, either for normal biological functions, pathogenic processes or pharmacological responses to therapeutic interventions (Atkinson et al., 2001). In fact, when new MRI methods are proposed as imaging biomarkers of particular diseases, it is crucial that they are validated against histopathology. In humans, such validation is limited to a biopsy, which is the gold standard of diagnosis for most types of cancer. Some types of biopsies can take an image-guided approach using MRI, Computed Tomography (CT) or Ultrasound (US). However, a biopsy may miss the most malignant region of the tumour and is difficult to repeat. Biomarker validation can be performed in preclinical disease models, where the animal can be terminated immediately after imaging for histological analysis. Here, in principle, co-registration of the biomarker images with the histopathology would allow for direct validation. However, in practice, most preclinical validation studies have been limited to using simple visual comparisons to assess the correlation between the imaging biomarker and underlying histopathology.
First objective (Chapter 5): Histopathology is the gold standard for assessing non-invasive imaging biomarkers, with most validation approaches involving a qualitative visual inspection. To allow a more quantitative analysis, previous studies have attempted to co-register MRI with histology. However, these studies have focused on developing better algorithms to deal with the distortions common in histology sections. By contrast, we have taken an approach to improve the quality of the histological processing and analysis, for example, by taking into account the imaging slice orientation and thickness. Multiple histology sections were cut in the MR imaging plane to produce a Stacked In-plane Histology (SIH) map. This approach, which is applied to the next two objectives, creates a histopathology map which can be used as the gold standard to quantitatively validate imaging biomarkers.
Second objective (Chapter 6): Glioblastoma is the most malignant form of primary brain tumour and recurrence following treatment is common. Non-invasive MR imaging is an important component of brain tumour diagnosis and treatment planning. Unfortunately, clinic MRI (T1W, T2W, CE-T1, and FLAIR) fails to detect regions of glioblastoma cell infiltration beyond the solid tumour region identified by contrast enhanced T1 scans. However, advanced MRI techniques such as Arterial Spin Labelling (ASL) could provide us with extra information (perfusion) which may allow better detection of infiltration. In order to assess whether local perfusion perturbation could provide a useful biomarker for glioblastoma cell infiltration, we quantitatively analysed the correlation between perfusion MRI (ASL) and stacked in-plane histology. This work used a mouse model of glioblastoma that mimics the infiltrative behaviour found in human patients. The results demonstrate the ability of perfusion imaging to probe regions of low tumour cell infiltration, while confirming the sensitivity limitations of clinic imaging modalities.
Third objective (Chapter 7): It is widely hypothesised that Multiparametric MRI (mpMRI), can extract more information than is obtained from the constituent individual MR images, by reconstructing a single map that contains complementary information. Using the MRI and histology dataset from objective 2, we used a multi-regression algorithm to reconstruct a single map which was highly correlated (r>0.6) with histology. The results are promising, showing that mpMRI can better predict the whole tumour region, including the region of tumour cell infiltration
AN INVESTIGATION OF ACADEMIC WRITING PROBLEMS LEVEL FACED BY UNDERGRADUATE STUDENTS AT AL IMAM AL MAHDI UNIVERSITY- SUDAN
Academic writing skills mostly involve the linguistic competence development of the students which many English Second Language learners may identify it as a challenging task. The main objective of this study is to look into various challenges encountered by English Second language students in academic writing in ordinary graduation project in the context of universities. Specifically, this research focuses on identifying the problems faced by the Arts Colleges within the University of Al Imam Al Mahdi, Sudan. The researcher used the student’s project graduation to investigate the problems encountered by the students when they used their academic writing skills. To state the obstacles recognized by the examined students in academic writing skills, the researcher employed a descriptive method. The findings of this research revealed the most problematic area faced by the students. Finally, the results of this research may help the scholars to reflect on teaching practices and urge the goverment to help teachers’ attempts to enhance the academic writing skills of their students at the University of Al Imam Al Mahdi, Sudan. Keywords: academic writing, students, problems
IDENTIFICATION OF STUDENTS AT RISK OF LOW PERFORMANCE BY COMBINING RULE-BASED MODELS, ENHANCED MACHINE LEARNING, AND KNOWLEDGE GRAPH TECHNIQUES
Technologies and online learning platforms have changed the contemporary educational paradigm, giving institutions more alternatives in a complex and competitive environment. Online learning platforms, learning-based analytics, and data mining tools are increasingly complementing and replacing traditional education techniques. However, academic underachievement, graduation delays, and student dropouts remain common problems in educational institutions. One potential method of preventing these issues is by predicting student performance through the use of institution data and advanced technologies. However, to date, scholars have yet to develop a module that can accurately predict students’ academic achievement and commitment. This dissertation attempts to bridge that gap by presenting a framework that allows instructors to achieve four goals: (1) track and monitor the performance of each student on their course, (2) identify at-risk students during the earliest stages of the course progression (3), enhance the accuracy with which at-risk student performance is predicted, and (4) improve the accuracy of student ranking and development of personalized learning interventions. These goals are achieved via four objectives. Objective One proposes a rule-based strategy and risk factor flag to warn instructors about at-risk students. Objective Two classifies at-risk students using an explainable ML-based model and rule-based approach. It also offers remedial strategies for at-risk students at each checkpoint to address their weaknesses. Objective Three uses ML-based models, GCNs, and knowledge graphs to enhance the prediction results. Objective Four predicts students’ ranking using ML-based models and clustering-based KGEs with the aim of developing personalized learning interventions. It is anticipated that the solution presented in this dissertation will help educational institutions identify and analyze at-risk students on a course-by-course basis and, thereby, minimize course failure rates
Al-Munşif min al-Kalām 'alā Mughnī lbn Hishãm by Taqï al-Dīn al-Shumunnī [d. 1468]
Ibn Hishām al-Ansārī is considered one of the most outstanding figures to have appeared in the history of the field of Arabic grammar. Thus, some biographers compare him to the illustrious Sîbawayh. The greatest of all Ibn Hishām's works is without doubt Mughni al-Labīb 'an Kutub al-A 'ārīb, written by the author for the benefit of fellow scholars and researchers, and not for beginners or regular students. A number of scholars have undertaken to write commentaries on this work, the most famous of these being Ibn al-Sā'igh and al-Damāmīnī. These were followed by al-Shumunnī, who intended his explanation to be a judgment between these two commentaries and the book of Ibn Hishām on their points on which they disputed. Nevertheless, except for an old uncritical edition dating from 1888, none of these commentaries has been published, despite their profound importance. The aim of the current research is thus primarily to bring into the open, in a modem academic style, a portion of the commentary on Mughriī al-Labīb known as al-Munşif min al-Kalām 'alā Mughriī Ibn Hishãm, written by Taqï al-Dīn al- Shumunnī; something not previously seen for this work. Considering the great size of the work, I have restricted myself to just a part of it, equaling about a third of the text, while hoping that my future endeavors will be primarily aimed at completing the work. In addition, the current thesis consists of an academic study consisting o
Comparative advantage of various regions in the world economy
The study would like to make comparism in the international comparative advantages for the developing
economic structure concerning the capital, skilled and unskilled human resources of the main economies and
country-groups in order to realise the sustainable development. According to Salvatore, Dominic, who
emphasized some principles of theory of comparative advantage accompanying his opinions, namely most
nations would like to realise free trade for themselves in order to get better profit and price incomes and most of
them continue to impose many restrictions on international trade.
The US has the most favourable Revealed Comparative Advantage in the world economy, even against Japan
and EU in field of capital and skilled workers. After the US, Japan has more comparative advantage against the
EU. From three highly developed regions the EU is the last one. Based on the country – groups, in United States
the capital was 0.11, skilled 0.06 and unskilled -0.30. In European Union capital was 0.03, skilled 0.01, unskilled
-0.06, in the same time in Japan capital was 0.07, skilled 0.15 and unskilled was -0.50 according to field of
Revealed Comparative Advantages.
Also in spite that OPEC countries have somehow little more favourable positions than other developing
countries, they have so mush high level of unskilled workers and considerable less skilled workers. In Eastern
Europe including Russia, capital was - 0.08, skilled -0.31, unskilled 0.36. In OPEC capital was - 0.09, skilled -0.29, unskilled 0.45. Their position is little similar than the Eastern Europe, including Russia, in filed of
Revealed Comparative Advantages.
The data show that the highly developed countries can play role for the future sustainable development and
economic growth based on the skilled human resources, which help the innovation development. The innovation
development can not be realised without skilled human resources. Also free flow of four elements results in
decreasing of expanditures of production, including the labour force, as employee, finally takes possibility to
achieve higher level of work efficiancy with using skilled workers, advanced technology and R&D – research
and development - to ensure competitive position either on the world market or local markets
The Complications of Learning and Understanding English Prepositions among Students at AL Imam AL Mahdi University in Sudan
The purpose of this study is to show the difficulties and analyze the various problems Sudanese students in the Arts College in the University of AL Imam AL Mahdi, face while learning and comprehending English prepositions. The focus of this study is therefore, on categorizing the types of challenges faced by these students. The research methods used were a survey followed by a report based on the results of the survey. The survey which comprised 12 items, explored the types of challenges faced by the respondents while learning the English prepositions. To portray the types of challenges faced by the students, the survey responses were analyzed and reported. In the report, the researcher described the problems and also suggested recommendations on the ways to overcome the challenges faced by the students. Thus, the findings of the study portrayed the factors which contributed to the problems in learning prepositions and also the ways to overcome these challenges. It is hoped that the findings of this survey and the suggested recommendations, will assist teachers in their classroom teaching of prepositions in the University of AL Imam AL Mahdi
Involving Parents in CALL: An Empirical Study
The study examined Computer Assisted Language Learning (CALL) together with parental participation on Saudi students’ English language achievement. A teaching-learning software, pre-posttest, observation checklist, and semi-structured interviews were constructed. Two intermediate sections with 25 students at each took part in the study. The study reported the effectiveness of parental involvement on students’ overall performance in English language learning. Key words: EFL, CALL, Intermediate class, Parental participation, Saudi Arabia
SUDANESE STUDENTS’ PERCEPTIONS OF USING FACEBOOK FOR VOCABULARY LEARNING AT UNIVERSITY LEVEL
This paper aims to explore Sudanese students’ perception of using Facebook for vocabulary learning at university level. Numerous studies have undertaken exploration on the use of innovative methodologies for foreign language learning. However, the role of Facebook in such context is underexplored, culminating in this particular work. 100 first and second year students pursuing their Bachelor degree with major in English at University of AL Imam AL Mahdi of the academic year 2016-2017 were selected to take part in this study. Quantitative research method was utilized to yield perspective understanding of their involvement with the particular platform. The findings reveal that the students have positive perceptions regarding the use of Facebook for vocabulary learning. The students have also expressed the assistance of Facebook in learning new things through the useful information available on the site. This paper concludes that Facebook is a potential platform for improvement of university students’ vocabulary knowledge. Keywords: Facebook, language learning, social media, Sudan, vocabulary, tertiary educationCite as: Al Mubarak, A.A. (2017). Sudanese students’ perceptions of using Facebook for vocabulary learning at university level. Journal of Nusantara Studies, 2(1), 170-176. http://dx.doi.org/10.24200/jonus.vol2iss1pp177-19
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