Numerical modelling of a 1.5 MW tidal turbine in realistic coupled wave–current sea states for the assessment of turbine hub-depth impacts on mechanical loads

This paper considers hub-depth impacts on mechanical loads for a tidal turbine operating in realistic coupled wave–current sea states. A novel medium-fidelity actuator-line CFD model for simulating tidal turbine non-steady hydrodynamic rotor load responses in the presence of turbulence, shear, and surface waves is developed. The model is validated using tank testing data from a lab-scale turbine. The validated model is then upscaled, to a power rating of 1.5 MW, and simulated in realistic wave–current conditions consistent with those of the MeyGen site. Mean torque and thrust are found to increase with turbine hub height, and the presence of waves is shown to increase mean torque and thrust values by up to 22% and 11%, respectively. The effect on standard deviations and maximum values for these variables is more pronounced, with increases of up to 2500% and 1700% in signal standard deviations, and up to 80% and 30% in maximum values for torque and thrust, respectively. The presence of longer period waves is also shown to reduce mean torque levels, while the corresponding standard deviations and maximum values remained relatively unchanged. In such circumstances, the turbine is operating with an undesirable combination of low-power and high-fatigue. Tidal turbine hub loading characteristics and sensitivities, in the context of the operational loads which subsequently enter the drivetrain and turbine support structure, are also analysed. The magnitude of out-of-plane rotor moments are found to increase with the hub height and wave height. Complex flow interactions are shown to play an important role in this context, leading to what is termed “wave-driven moment-type dominance” effects. Overall, both the rotor location and wave composition are found to significantly impact the turbine’s rotor mechanical load response

Isolation and Identification of Helicase from Anoxybacillus sp for DNA amplification

AbstractHelicase-producing thermophilic microorganisms were successfully isolated from water samples collected from hot springs in the from Ulu Legong Hot spring, Kedah, Malaysia and were identified up to genus level. The light and scanning microscopy technique were used to identify the morphology of the isolate. Chromosomal DNA from the organism was isolated and used to amplify 16S rRNA and UvrD gene fragments. The gene was amplified by a set of universal primers (F_UNI16S and R_UNI16S). The phylogenetic tree, homological analysis, and detailed comparison of the sequences showed that 16S rRNA gene sequence of the isolate had closest similarities with Anoxybacillus sp. Isolates gave PCR fragments of 2149bp which represent the UvrD gene and 1500bp which represent the 16S rRNA respectively of Anoxybacillus. Anoxybacillus sp was successfully isolated and identified by using 16S rRNA gene sequence analysis with UvrD gene

DC Link Capacitor Voltage of D-Statcom With Fuzzy Logic Supervision

In a DSTATCOM, generally, the dc capacitor voltage is regulated using a PI controller when various control algorithms are used for load compensation. However, during load changes, there is considerable variation in dc capacitor voltage which might affect compensation. In this work, a fuzzy logic based supervisory method is proposed to improve transient performance of the dc link. The fuzzy logic based supervisor varies the proportional and integral gains of the PI controller during the transient period immediately after a load change. An improvement in the performance of the controller is obtained because of appropriate variation of PI gains using expert Knowledge of system behaviour and higher sampling during the transient period. A 50% reduction in the error in dc link capacitor voltage during load change compared to a normal PI-controller is obtained. The voltage waveform also has a faster settling time. The efficacy of the proposed strategy is proved using detailed simulation studies

Isolation and identification of Candida albicans to produce in house helicase for PCR

Candida albicans is a dimorphic fungus that can grow in a wide range of temperature. In such case, this microorganism has the potential to produce enzymes that able to function at elevated temperature. These enzymes are also essential in the field of molecular biology and recombinant technologies. Therefore, the enzymes produced by Candida albicans could be applied in the polymerase chain reaction (PCR). The PCR is the most widely used in DNA amplification. In this study, Candida spp. were successfully isolated and collected from Hospital Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia. Different culture media were used to identify the morphology of colony. Based on the colonies growth on chromogenic agar, Candida sp. was identified. Microscopic examination (light and scanning microscopy) was carried out to identify the morphology of the isolate. A presumptive identification of germ tube test was performed to find out the dimorphic and pathogenicity characteristic of isolate. The formation of germ tubes from the isolate showed positive result of Candida albicans. A commercial Analytical Profile Index (API) Candida identification kit was used in this study as a phenotypic identification of Candida sp. The result of API Candida was confirmed that the isolate was the Candida albicans. Candida albicans was successfully isolated and identified phenotypically in this study for future in house helicase production

Flood Prediction using MLP, CATBOOST and Extra-Tree Classifier

Flooding can be one of the many devastating natural catastrophes, resulting in the annihilation of life and damaging property. Additionally, it can harm farmland and kill growing crops and trees. Nowadays, rivers and lakes are being destroyed, and the natural water reservoirs are converted into development sites and buildings. Due to this, even just a bit of rain can cause a flood. To minimize the number of fatalities, property losses, and other flood-related issues, an early flood forecast is necessary. Therefore, machine learning methods can be used for the prediction of floods.To forecast the frequency of floods brought on by rainfall, a forecasting system is built using rainfall data. The dataset is trained using various techniques like the MLP classifier, the CatBoost classifier, and the Extra-Tree classifier to predict the occurrence of floods. Finally, the three models' performances are compared and the best model for flood prediction is presented. The MLP, Extra-Tree, and CatBoost models achieved accuracy of 94.5%, 97.9%, and 98.34%, respectively, and it is observed that CatBoost performed well with high accuracy to predict the occurrence of floods

Cloudbus Toolkit for Market-Oriented Cloud Computing

This keynote paper: (1) presents the 21st century vision of computing and identifies various IT paradigms promising to deliver computing as a utility; (2) defines the architecture for creating market-oriented Clouds and computing atmosphere by leveraging technologies such as virtual machines; (3) provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; (4) presents the work carried out as part of our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a Platform as a Service software system containing SDK (Software Development Kit) for construction of Cloud applications and deployment on private or public Clouds, in addition to supporting market-oriented resource management; (ii) internetworking of Clouds for dynamic creation of federated computing environments for scaling of elastic applications; (iii) creation of 3rd party Cloud brokering services for building content delivery networks and e-Science applications and their deployment on capabilities of IaaS providers such as Amazon along with Grid mashups; (iv) CloudSim supporting modelling and simulation of Clouds for performance studies; (v) Energy Efficient Resource Allocation Mechanisms and Techniques for creation and management of Green Clouds; and (vi) pathways for future research.Comment: 21 pages, 6 figures, 2 tables, Conference pape

The Exponential Rise of Teledentistry and Patient-Oriented Protective Measures in Southeast Asian Dental Clinics: Concerns, Benefits, and Challenges

In the Southeast Asian region, various policies have been advocated by health regulatory bodies that entail protective measures such as face masks, gloves, maintaining distance in public areas, and more. These protective measures are aimed at helping reverse the growth rate of the coronavirus. Dentists in this region have incorporated several changes to their practices to help minimize risks of person-to-person transmission inside dental offices. This narrative review aimed to provide an in-depth overview of the current situation in the Southeast Asian region regarding the use of teledentistry during the pandemic. Teledentistry involves the transfer of patient information across remote distances for online consultation and treatment planning. A few years back, it used to be a lesser-known entity but has seen an exponential rise in its incorporation into dental practices all around the Association of Southeast Nations (ASEAN) region. Many clinics in the Southeast Asian region have started using online consultations to ensure that patients can be diagnosed or followed up during their treatment. Teledentistry is the clear answer in the coming months as it will help reduce the risk of virus transmission and help patients get access to oral healthcare and dentists to see their patients. This article reviews the current pandemic situation in the ASEAN region, the recent evidence, and the scope of teledentistry. It also provides recommendations for the future and sheds light on the different types of teledentistry and how it can be incorporated into practices by regulatory authorities in this region

A randomized controlled trial of quetiapine versus placebo in the treatment of delirium

Background Delirium is a commonly occurring complex neuropsychiatric disorder. Evidence for its treatment based on randomized controlled trials (RCTs) is poor. Aims To determine the efficacy and acceptability of quetiapine in the treatment of delirium. Method A double-blind, RCT was conducted. A total of 42 patients were randomized to quetiapine or a placebo group. The primary outcome measure was the Delirium Rating Scale Revised 98. Other scales used were the Brief Psychiatric Rating Scale, Mini-Mental State Examination and Clinical Global Improvement. In order to account for missing data, a nonlinear mixed-effects model was used to estimate the difference between the two groups. Results The quetiapine group improved more rapidly than the placebo group. Specifically, the quetiapine group recovered 82.7% faster (S.E. 37.1%, P=.026) than the placebo group in terms of DRS-R-98 severity score. In terms of the DRS-R-98 noncognitive subscale, the quetiapine group improved 57.7% faster (S.E. 29.2%, P=.048) than the placebo group. Conclusions Quetiapine has the potential to more quickly reduce the severity of noncognitive aspects of delirium. This study was underpowered for treatment comparisons at specific points in time but nonetheless detected significant differences when analyzing the whole study period. While it is not possible to draw definitive conclusions, further larger studies exploring the use of quetiapine in other delirium populations seem justified. Larger increments in the dose of quetiapine may yield even stronger results

How IGF-II Binds to the Human Type 1 Insulin-like Growth Factor Receptor.

Human type 1 insulin-like growth factor receptor (IGF-1R) signals chiefly in response to the binding of insulin-like growth factor I. Relatively little is known about the role of insulin-like growth factor II signaling via IGF-1R, despite the affinity of insulin-like growth factor II for IGF-1R being within an order of magnitude of that of insulin-like growth factor I. Here, we describe the cryoelectron microscopy structure of insulin-like growth factor II bound to a leucine-zipper-stabilized IGF-1R ectodomain, determined in two conformations to a maximum average resolution of 3.2 Å. The two conformations differ in the relative separation of their respective points of membrane entry, and comparison with the structure of insulin-like growth factor I bound to IGF-1R reveals long-suspected differences in the way in which the critical C domain of the respective growth factors interact with IGF-1R