Cross-cultural Adaption and Psychometric Properties Testing of The Arabic Anterior Knee Pain Scale

Patellofemoral pain syndrome (PFP) is a common condition affecting the musculoskeletal system and has a tendency of becoming chronic and is problematic in the affected people. It is the commonest cause of anterior knee pain. In over 2/3 of the patients affected it has been successfully treated through the use of rehabilitation protocols which are designed in pain reduction and returning the functionality to an individual. Many cases of patellofemoral pain syndrome can be avoided only if a clinician can make a pre-diagnosis. Preparation Screening Evaluation testing done by a certified athletic trainer can also help in prevention of this syndrome. The purpose of this topic is to be able to review the anatomy of the knee, the risk factors predisposing to patellofemoral pain syndrome, soft tissue, arterial system, innervation of the patellofemoral joint and strategies for rehabilitation. This will enable reviewing the anatomy of the knee, relationships between arterial collateralization, nerve supply and alignment of soft tissues in explaining the mechanisms that lead to this syndrome. By doing so, it will help in the future whereby using different treatments that will be aiming at the non-soft tissue that cause patellofemoral pain syndrome

Deep Learning for Electricity Forecasting Using Time Series Data

The complexity and nonlinearities of the modern power grid render traditional physical modeling and mathematical computation unrealistic. AI and predictive machine learning techniques allow for accurate and efficient system modeling and analysis. Electricity consumption forecasting is highly valuable in energy management and sustainability research. Furthermore, accurate energy forecasting can be used to optimize energy allocation. This thesis introduces Deep Learning models including the Convolutional Neural Network (CNN), the Recurrent neural network (RNN), and Long Short-Term memory (LSTM). The Hourly Usage of Energy (HUE) dataset for buildings in British Columbia is used as an example for our investigation, as the dataset contains data from residential customers of BC Hydro, a provincial power utility company. Due to the temporal dependency in time-series observation data, data preprocessing is required before a model can be created. The LSTM model is utilized to create a predictive model for electricity consumption as output. Approximately 63% of the data is used for training, and the remaining 37% is used for testing. Various LSTM parameters are tested and tuned for best performance. Our LSTM predictive model can facilitate power companies’ resource management decisions

Identifying and characterizing lysosomal storage disease phenotypes for utilization in novel screening and monitoring assays

In the lysosomal storage disease (LSD) field there are very few studies examining large cohorts of LSD samples in order to identify suitable new pan-LSD biomarkers and identify pan-LSD disease mechanisms. This thesis investigated the possibility of using a simple fluorimetric test for lysosomal swelling, simple enzyme assays and the associated accumulation of storage material alongside the presence of unique heavy metal accumulation to identify the majority of LSDs. The results showed that lysosomal swelling is a highly sensitive phenotype and that high-throughput analysis can be achieved using the fluorescent marker lysotracker. This probe can be used to screen LSD cells as both a suitable biomarker and potentially for drug screening to develop new treatments for LSDs. This thesis was also identified that secondary alteration of lysosomal enzymes is a common feature of LSDs. Such secondary lysosomal enzyme alteration could be useful for treatment monitoring and some novel biomarkers for some and potentially all of the LSDs have emerged. I have also conducted the first electron microscopy (EM) study that compares all classes of LSDs. This technique was proven to be useful for characterisation of the lipids and other macromolecules stored both primarily and secondarily in the majority of LSDs. EM also confirmed that alteration of secondary lysosomal enzymes could be the reason behind the accumulation of materials in some LSDs. Divalent cation signalling defects have been reported in several LSDs, I therefore studied Ca2+ and trace element (TEs) ion changes across all the LSDs and discovered that lysosomal Ca2+ defects are common and that changes in Zn2+ and a few other TEs were identified in almost all or specifically altered in some of the LSDs respectively. Our results highlight the possibility of using inductively coupled plasma mass spectrometry (ICP-MS) for monitoring changes in blood TE levels during the course of clinical treatment of CLN5 patients. Finally, evidence points to the NPC1 protein function, in terms of Zn2+ efflux from lysosomes, was inhibited by common storage of sphingoid bases and is a common phenotype across the majority of LSDs that explains the occurrence of secondary lipid accumulation across most of the LSDs. Our findings provide new potential biomarkers, new mechanisms of pathogenesis and new therapeutic targets that are common to all of the LSDs validating the power of studying multiple LSDs together

Examining the existing reality of using social media as e-learning tools at an Emerging University in Saudi Arabia from the viewpoint of tutors and students

Social media has become an integral part of today’s societies across the globe. As a consequence, the use of social media in higher education is rapidly expanding, both amongst students and faculties. Saudi Arabia’s higher education is no exception. This study examines dimensions of the reality of social media use in an EU in Saudi Arabia in order to provide a new understanding that supports the effective integration of these tools in higher education. The theoretical basis for this study was developed from Bandura’s Social Learning Theory and Davis’ Technology Acceptance Model and explored social media use from the viewpoints of tutors and students. The study employed a concurrent mixed-methods design. Firstly, 407 students and 290 tutors completed questionnaires, and then, to increase validity and reliability, 10 of the tutors were then interviewed. The data were analysed separately, then compared and integrated to identify key results. The findings reveal that the students and tutors who participated in this study had positive perceptions of the use of social media in education. Moreover, a great number of students were highly dependent on social media and viewed these tools as supportive and useful for facilitating learning, communicating, enhancing collaboration, exchanging experiences, generating and improving content, and constructing knowledge. Many tutors expressed the view that they could see the benefit of students interacting with and learning from others through social media. Nevertheless, a large portion of the faculty did not use social media for instructional purposes. The results also indicate that the major barriers to implementing social media tools in higher educational institutions are their potential for distraction, the need for training, privacy issues, and cyber-bullying. These findings highlight the fact that, as social media tools continue to attract student attention, more research needs to be done on the impact of social media on: • student collaboration and social interaction within the learning environment; • student collaboration with tutors; • the ways in which the different types of SM affect student learning and performance; • the negative impact of SMTs on learning environments and how this may also affect student learning and academic performance; and • the different barriers that students and tutors face when they utilise SM for learning, especially regarding their perceptions of privacy and security issues when using web-based applications

Effect of proinflammatory cytokines on lung and intestinal mucosal permeability in vitro

Transport of therapeutics across mucosal barriers provides an attractive route for non-invasive drug delivery, if sufficient drug permeability can be achieved. In inflammatory conditions of the epithelial mucosa, the barrier characteristics were observed to be modified with the permeability of noxious molecules increased significantly due to, at least in part, elevated levels of proinflammatory cytokines leading to tight junction disruption. This work aims to investigate the effect of selected cytokines on the barrier characteristics of airway and intestinal cell cultures in vitro in order to improve the understanding of transport features across inflamed epithelial cell layers. Data indicated that a three-four days short-term treatment with tumor necrosis factors-alpha (TNF-α) produced a significant effect on Calu-3 cell layers and some effect on Caco-2 cells, as shown by decreased transepithelial resistance (TEER values and increased permeability of model permeant (fluorescein isothiocyanate dextran with molecular weight of 10kDa, FD10). On the other hand, short-term treatments with proinflammatory cytokines interleukin-4 and interleukin-13 IL-4 and IL-13 did not show significant effects on the tested cell lines. Combined effect of cytokines was shown to cause a significant effect on Calu-3 apparent permeability coefficient (Papp) when the combination contains TNF-α, while the Papp across Caco-2 layers was observed to be influenced by IL-4/IL-13 combination; the effect being reduced when TNF-α was present. In the situation of long-term treatment (for the duration of cell culture), IL-4 and IL-13 did not produce a significant effect on TEER and Papp for both cell lines when incubated for 21 days. TNF-α however produced a significant effect on FD10 permeability across layers of both cell lines. Finally, the work examined the expression features of tight junction proteins (TJP2 and TJP3) and endocytosis pathway components (LAMP1, RAB4A, and RAB5A) in the cell layers following a prolonged exposure to the proinflammatory mediator TNF-α. Results demonstrated that expression of the tested TJ proteins was downregulated, though endocytosis related proteins did not show alteration in their expression. These results therefore indicated that the presence of proinflammatory cytokines could be involved in the improvement in the transport of macromolecules through epithelial mucosa by affecting a TJ opening

Blind Estimation of Multi-Path and Multi-User Spread Spectrum Channels and Jammer Excision via the Evolutionary Spectral Theory

Despite the significant advantages of direct sequence spreadspectrum communications, whenever the number of users increases orthe received signal is corrupted by an intentional jammer signal,it is necessary to model and estimate the channel effects in orderto equalize the received signal, as well as to excise the jammingsignals from it. Due to multi-path and Doppler effects in thetransmission channels, they are modeled as random, time-varyingsystems. Considering a wide sense stationary channel during thetransmission of a number of bits, a linear time-varying modelcharacterized by a random number of paths, each beingcharacterized by a delay, an attenuation factor and a Dopplerfrequency shift, is shown to be an appropriate channel model. Itis shown that the estimation of the parameters of such models ispossible by means of the spreading function, related to thetime-varying frequency response of the system and the associatedevolutionary kernels. Applying the time-frequency orfrequency-frequency discrete evolutionary transforms, we show thata blind estimation procedure is possible by computing thespreading function from the discrete evolutionary transform ofthe received signal. The estimation also requires the synchronizedpseudo-noise sequence for either of the users we are interestedin. The estimation procedure requires to adaptively implementingthe discrete evolutionary transform to estimate the spreadingfunction and determine the channel parameters. Once the number ofpaths, delays, Doppler frequencies and attenuations characterizingthe channel are found, a decision parameter can be obtained todetermine the transmitted bit. We will show also that ourestimation approach supports multiuser communication applicationssuch as uplink and downlink in wireless communicationtransmissions. In the case of an intentional jamming, common inmilitary applications, we consider a receiver based onnon-stationary Wiener masking that excises such jammer as well asinterference from other users. Both the mask and the optimalestimator are obtained from the discrete evolutionarytransformation. The estimated parameters from the computedspreading function, corresponding to the closest to the line ofsight signal path, provide an efficient detection scheme. Ourprocedures are illustrated with simulations, that display thebit-error rate for different levels of channel noise and jammersignals