This paper reviews the advances made on studies related to bank erosion. Bank erosion has been an area of interest by researchers in geological, geotechnical, hydraulic, hydrology and river engineering disciplines. With anticipated global challenges from climate change impacts, bank erosion studies could support challenges faced in ensuring sustainable environmental management. The evolution in the theoretical and laboratory findings have led to the advances in bank erosion and contributed to new knowledge in the said field. This review summarises the findings of previous investigators including measurements approach and prediction of rates of bank erosion through the use of physical models and numerical approach.
This study proposed a novel application of Neural Network AutoRegressive eXogenous (NNARX) model in predicting nonlinear behaviour of riverbank erosion rates which is difficult to be achieved with good accuracy using conventional approaches. This model can estimate complex river bank erosion rates with flow variations. The NNARX model analysed to a set of primary data, 60% (203 data for training) and 40% (135 data for testing), which were collected from Sg. Bernam, Malaysia. A set of nondimensional parameters, known as functional relationship, used as an input to the NNARX model has been established using the method of repeating variables. The One-Step-Ahead time series prediction plots are used to assess the accuracy of all developed models. Model no. 6 (5 independent variables with 10 hidden layers) gives good predictive performance, supported by the graphical analysis with discrepancy ratio of 94% and 90% for training and testing datasets. This finding is consistent with model accuracy result, where Model no. 6 achieved R2 of 0.932 and 0.788 for training and testing datasets, respectively. Result shows that bank erosion is maximized when the near-bank velocity between 0.2 and 0.5 m/s, and the riverbank erosion is between 1.5 and 1.8 m/year. On the other hand, higher velocities ranging from 0.8 to 1.3 m/s induces erosion at a rate between 0.1 and 0.4 m/year. Sensitivity analysis shows that the highest accuracy of 91% is given by the ratio of shear velocity to near-bank velocity followed by boundary shear stress to near-bank velocity ratio (88.5%) and critical shear stress to near-bank velocity ratio (88.2%). It is concluded that the developed model has accurately predicted non-linear behaviour of riverbank erosion rates with flow variations. The study's findings provide valuable insights in advanced simulations and predictions of channel migration, encompassing both lateral and vertical movements, the repercussions on the adjacent river corridor, assessing the extent of land degradation and in formulating plans for effective riverbank protection and management measures.
Sleep quality can vary in relation to one’s general well-being and in the elderly, it is often affected by the presence of medical or psychological conditions. This study aims to determine the frequency of different components of sleep quality in the elderly, and their relationships with psychosocial and medical attributes. A cross-sectional study was conducted on 123 attendees aged 60 years and above at Pusat Perubatan Primer Universiti Kebangsaan Malaysia. Sleep quality and psychological distress were assessed using the validated Malay versions of Pittsburgh sleep quality index (PSQI) and Hamilton anxiety depression scale (HADS) respectively. Information on medical comorbidities and medications were obtained from the participants, their doctors and medical notes. Almost half of the patients experienced poor sleep quality (47.2%) which was significantly associated with older mean age (69.5 ±4.55). There was no statistical significance between sleep quality and other sociodemographic characteristics (gender, ethnicity and living arrangement). Most patients described their sleep quality as subjectively generally “fairly good” (69.1%) despite PSQI scores indicating poor sleep quality. A majority of the patients (59.3%) were on follow-up for 3 or more medical illnesses, with heart disease as the only medical comorbidity significantly associated with poor sleep quality. Most of them also complained of only “mild difficulty” with their sleep. Among the 7 sleep components of PSQI, “sleep disturbance” was the most frequent experience. Most experienced mild sleep disturbance (87.8%) and usage of hypnotic agents was low (6.5%). Only 23.6% of patients had significant psychological distress (HADS scores ≥ 8), with positive correlation with sleep quality.
Study site: Pusat Perubatan Primer, Universiti Kebangsaan Malaysia (PPPUKM), Kuala Lumpur, Malaysia