Oceans and COVID-19: perspectives, reflections, recovery and regulatory frameworks

COVID-19 pandemic has created an unprecedented public health crisis, taken about 1.4 million lives so far, infected almost 70 million people around the world, battered the global economy and paralyzed the normal activity. This situation is evolving so rapidly that the data on numbers of infections and deaths are changing daily and the economic impacts are difficult to evaluate at this stage and probably will not be exactly known in the near future. It is important to determine the genesis of the outbreak to understand the root causes of COVID-19 and to prevent such pandemics from occurring in the future. It is believed that the virus originated in a seafood market in Wuhan (China) that was also trading in wildlife for human consumption. Such practices are associated with the habitat degradation and biodiversity loss, leading to an imbalance of the natural ecosystems. The zoonotic spillover of this infectious outbreak is a reflection of the impairment of natural systems. Scientific and anecdotal evidences demonstrate the significance of marine critical habitats in combating and containing human diseases. There are many other ways in which the oceans can help in human health. In addition to providing an analysis of the COVID-19 outbreak, this paper also suggests knowledge-based and informed measures that need to be applied to prevent a repeat of such catastrophic events while highlighting the role of oceans in this context. Plans and strategies for recovering the global economy and ensuring its resilience will require incorporating nature-based solutions and ecosystem restoration. The sustainability of the ocean is a key consideration in the development of a framework for post-COVID-19 recovery and this aspect is the major focus of this paper

Early mobilisation in critically ill COVID-19 patients: a subanalysis of the ESICM-initiated UNITE-COVID observational study

Background Early mobilisation (EM) is an intervention that may improve the outcome of critically ill patients. There is limited data on EM in COVID-19 patients and its use during the first pandemic wave. Methods This is a pre-planned subanalysis of the ESICM UNITE-COVID, an international multicenter observational study involving critically ill COVID-19 patients in the ICU between February 15th and May 15th, 2020. We analysed variables associated with the initiation of EM (within 72 h of ICU admission) and explored the impact of EM on mortality, ICU and hospital length of stay, as well as discharge location. Statistical analyses were done using (generalised) linear mixed-effect models and ANOVAs. Results Mobilisation data from 4190 patients from 280 ICUs in 45 countries were analysed. 1114 (26.6%) of these patients received mobilisation within 72 h after ICU admission; 3076 (73.4%) did not. In our analysis of factors associated with EM, mechanical ventilation at admission (OR 0.29; 95% CI 0.25, 0.35; p = 0.001), higher age (OR 0.99; 95% CI 0.98, 1.00; p ≤ 0.001), pre-existing asthma (OR 0.84; 95% CI 0.73, 0.98; p = 0.028), and pre-existing kidney disease (OR 0.84; 95% CI 0.71, 0.99; p = 0.036) were negatively associated with the initiation of EM. EM was associated with a higher chance of being discharged home (OR 1.31; 95% CI 1.08, 1.58; p = 0.007) but was not associated with length of stay in ICU (adj. difference 0.91 days; 95% CI − 0.47, 1.37, p = 0.34) and hospital (adj. difference 1.4 days; 95% CI − 0.62, 2.35, p = 0.24) or mortality (OR 0.88; 95% CI 0.7, 1.09, p = 0.24) when adjusted for covariates. Conclusions Our findings demonstrate that a quarter of COVID-19 patients received EM. There was no association found between EM in COVID-19 patients' ICU and hospital length of stay or mortality. However, EM in COVID-19 patients was associated with increased odds of being discharged home rather than to a care facility. Trial registration ClinicalTrials.gov: NCT04836065 (retrospectively registered April 8th 2021)

Detection of natural radioactive materials in the soil of bauxite mining areas of Kuantan, Pahang, Malaysia

Natural radionuclides, such as, Uranium (U-238), Thorium (Th-236), Radium (Ra-226) and Potassium (K-40) are present in the soil. In this study the detection of natural radioactive materials in the soil of bauxite mining areas in Kuantan was determined. Soil samples were collected from three different places. Advanced Nuclear Spectroscopy System with UCS 30 Universal Computer Spectrometer Software and High Sensitivity Gamma Spectroscopy Model SE-9764 with WinDas Software were used. Background radiation energy spectra and soil samples were obtained and compared. The spectra obtained by measuring all samples show the similar pattern as recorded from the background radiation measurement. Therefore, this study evidenced the absence of radioactive elements in the collected soil samples of bauxite mining areas. However, results cannot be generalized for all bauxite mining areas of Kuantan district

Salp Swarm Optimization Algorithm-Based Controller for Dynamic Response and Power Quality Enhancement of an Islanded Microgrid

The islanded mode of the microgrid (MG) operation faces more power quality challenges as compared to grid-tied mode. Unlike the grid-tied MG operation, where the voltage magnitude and frequency of the power system are regulated by the utility grid, islanded mode does not share any connection with the utility grid. Hence, a proper control architecture of islanded MG is essential to control the voltage and frequency, including the power quality and optimal transient response during different operating conditions. Therefore, this study proposes an intelligent and robust controller for islanded MG, which can accomplish the above-mentioned tasks with the optimal transient response and power quality. The proposed controller utilizes the droop control in addition to the back to back proportional plus integral (PI) regulator-based voltage and current controllers in order to accomplish the mentioned control objectives efficiently. Furthermore, the intelligence of the one of the most modern soft computational optimization algorithms called salp swarm optimization algorithm (SSA) is utilized to select the best combination of the PI gains (kp and ki) and dc side capacitance (C), which in turn ensures optimal transient response during the distributed generator (DG) insertion and load change conditions. Finally, to evaluate the effectiveness of the proposed control approach, its outcomes are compared with that of the previous approaches used in recent literature on basis of transient response measures, quality of solution and power quality. The results prove the superiority of the proposed control scheme over that of the particle swarm optimization (PSO) and grasshopper optimization algorithm (GOA) based MG controllers for the same operating conditions and system configuration

Dynamic response enhancement of grid-tied ac microgrid using salp swarm optimization algorithm

To alleviate the overloads in the power system and to reduce the exponential growth in carbon dioxide (CO2) emissions, deployment of the renewable energy sources (RES) into the power system is the need of the hour. However, injecting these RES into the current power system network causes large voltage and power overshoots hence deteriorate the transient response and power quality of the overall power system. In this paper, an efficient solution of the above-mentioned issues is explored by developing an optimal microgrid (MG) controller using one of the most modern and intelligent artificial intelligence (AI) techniques named the salp swarm optimization algorithm (SSA). The intelligence of the SSA is exploited to select the optimal controller gains and dc-link capacitance value by minimizing a time integrating error fitness function (FF) which in-turn enhances the dynamic response and power quality of the studied MG system. The proposed grid-tied MG controller is designed to achieve the preset active and reactive power sharing ratio between distributed generator (DG) and utility grid during DG and load switching conditions. To validate the superiority of the proposed controller, its performance is compared with that of its precedent grasshopper optimization algorithm (GOA)-based controller for the identical operating conditions and system configuration. The outcomes of the study show that the proposed MG controller outperforms its competitor in terms of transient response and quality of power

An experimental study of tool wear during end milling of carbon fibre reinforced polymer in cutting fluid condition.

Carbon fibre reinforced polymer (CFRP) is replacing metallic components and become a valuable material that has been used in many industrial applications including biomedical, marine and automobile. This is due to their excellent performance in term of reliability, high strength and light weight. However, the machining of CFRP is challenging because the abrasiveness of their reinforcement component often resulted in high tool wear rate. This experiment was carried out to investigate the effect of cutting parameters (cutting speed and cutting condition) on tool wear of uncoated tungsten carbide end mill tool, and to observe the wear mechanism of the carbide tool mill during milling of CFRP. In this study, machining test was carried out with the presence of coolant to aid in removing the cutting heat during machining. The effect of cutting speed of 132 m/min, 151 m/min and 170 m/min with a constant feed rate of 2100 mm/min during milling process of CFRP by using uncoated tungsten carbide end mill tool were discussed. Based on the result obtained, it was found out that the value of tool wear at cutting speed of 170 m/min is higher compared to the wear value at cutting speed of 132 m/min due to the high frequency friction of tool against machined surface. Analysis of tool wear using Scanning Electron Microscope (SEM) found out that the primary wear observed is abrasive wear due to the rubbing action between the tool and the surface of workpiece. The cutting tool is observed to have the lowest tool wear when low cutting speed is implemented along with the presence of coolant

An experimental investigation on surface quality of CFRP after milling in cutting fluid environment

Carbon fiber reinforced polymer (CFRP) are becoming more widely used in replacing metallic component as it offers better strength-to-weight ratio compared to steel while having high corrosive resistance. Although CFRP have always been manufactured near to net-shape, secondary machining process is still required to achieve the final dimension. Machining can cause CFRP to experience surface defects such as delamination, fiber pull-out and smeared matrix which lead to part rejection. The aim of this study is to investigate the effect of cutting parameters on the surface roughness and its quality. In this investigation, cutting speeds of 132, 151 and 170 m/min with constant feed rate of 1800 mm/min were applied during end milling of CFRP using uncoated tungsten carbide end mill tool in cutting fluid condition. It was observed that high cutting speed (170 m/min) produced 45.3% lower Ra than lower cutting speed (132 m/min) after machining for 6500 mm cutting distance. The occurrence of thermally degraded resin on the machined surface was apparent at higher cutting distance between 3000 to 6500 mm. Also, it was observed that the smearing of thermally degraded resin was more obvious on higher cutting speed when compared at 132 m/min cutting speed suggesting that at higher cutting speed more heat generated that resulted in increasing the cutting temperature. Fiber pullout was also found on the machined surface and the cavity formation changes with increasing of cutting distance resulting in relatively larger cavity

Analysis on tool wear during milling carbon fiber reinforced polymer in dry, coolant and chilled air condition

The demand of the Carbon Fiber Reinforced Polymer (CFRP) has been significantly increasing over the years especially in automotive and aerospace since CFRP possesses an excellent strength-to-weight ratio. However, milling CFRP challenging due to its anisotropic and heterogeneous property therefore produce brittle and dust-like chips. As CFRP is a combination of layers of carbon fibers embedded in matrix resin, machining process must be conducted below the glass transition temperature (Tg) of the matrix resin as it can degrade the CFRP. In this experimentto investigate the effect of cutting speed and cutting conditions on the tool wear during the milling process, CFRP was machined with 6mm diameter uncoated tungsten carbide tool with helix angle of 30°. Milling of CFRP was performed with three cutting speeds of 130, 150 and 170 m/min in three different cutting conditions which is dry, coolant and chilled air with constant feed rate of 2100 mm/min and depth of cut of 2 mm. The highest average tool wear of 110 μm was obtained during milling the CFRP with cutting speed 170 m/min in chilled air condition, 25.5% higher than the average wear of 82 μm at low cutting speed of 130 m/min in the same condition

Swarm intelligence-based optimization techniques for dynamic response and power quality enhancement of ac microgrids: a comprehensive review

The increasing penetration of Microgrids (MGs) into existing power systems and 'plug and play' capability of Distributed Generators (DGs) causes large overshoots and settling times along with various power quality issues such as voltage and frequency flickers, current harmonics and short current transients. In this context, over the past few years, considerable research has been undertaken to investigate and address the mentioned issues using different control schemes in conjunction with soft computational techniques. The recent trends and advancements in the field of Artificial Intelligence (AI) have led the development of Swarm Intelligence (SI) based optimized controllers for smooth Renewable Energy Sources (RES) penetration and optimal voltage, frequency, and power-sharing regulation. Moreover, the recent studies have proved that the SI-based controllers provide enhanced dynamic response, optimized power quality and improved the dynamic stability of the MG systems as compared to the conventional control methods. Their importance in modern AC MG architectures can be judged from the growing number of publications in the recent past. However, literature, pertaining to SI applications to AC MG, is scattered with no comprehensive review on this significant development. As such, this study provides an overview of 15 different SI optimization techniques as applied to AC MG controls from 43 research publications including a detailed review of one of the elementary and most widely used SI based metaheuristic optimization algorithms called Particle Swarm Optimization (PSO) algorithm. This comprehensive review provides a valuable one-stop source of knowledge for the researchers and experts working on SI controller's applications for AC MG dynamic response and power quality improvements

Optimal Power Flow Controller for Grid-Connected Microgrids using Grasshopper Optimization Algorithm

Despite the vast benefits of integrating renewable energy sources (RES) with the utility grid, they pose stability and power quality problems when interconnected with the existing power system. This is due to the production of high voltages and current overshoots/undershoots during their injection or disconnection into/from the power system. In addition, the high harmonic distortion in the output voltage and current waveforms may also be observed due to the excessive inverter switching frequencies used for controlling distributed generator’s (DG) power output. Hence, the development of a robust and intelligent controller for the grid-connected microgrid (MG) is the need of the hour. As such, this paper aims to develop a robust and intelligent optimal power flow controller using a grasshopper optimization algorithm (GOA) to optimize the dynamic response and power quality of the grid-connected MG while sharing the desired amount of power with the grid. To validate the effectiveness of proposed GOA-based controller, its performance in achieving the desired power sharing ratio with optimal dynamic response and power quality is compared with that of its precedent particle swarm optimization (PSO)-based controller under MG injection and abrupt load change conditions. The proposed controller provides tremendous system’s dynamic response with minimum current harmonic distortion even at higher DG penetration levels