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Due to a lack of water treatment technology, developing and emerging nations have become significant polluters and water shortage is exacerbated by pollution. Ammonium toxicity is a huge global environmental concern with no clear solution. Population growth and industrialization destroy the ecosystem. Common and industrial products contain ammonium ions. Water pollution damages fish and other aquatic life. An inexpensive and green wastewater treatment method is adsorption. Adsorbent polymers that remove ammonium ions from wastewater have been explored. Ammonium ions are very hazardous when deposited into surface waters. Surfaces of bentonite and montmorillonite clay may attach sodium ammonium ions. They are cheap and abundant, therefore used to treat drain water. Bentonite outperformed montmorillonite in eliminating ammonium ions from water. Bentonite and montmorillonite clays were used to remove residual ammonium ions. These are utilized for bentonitic and montmorillonitic clays. Both clays were absorbed in a neutral pH, and it was free of sulfuric acid, ammonium ions, and phosphorus ions. Montmorillonitic clay boosted TDS by nearly 10% whereas bentonitic clay only raised TDS by 1%. Adsorption may inexpensively filter water and the surface charge of adsorbents affect their adsorption capacity. Ammonium ions may be recycled, and several bioreactors can remove ammonium ions from liquid and solid phases. Iterate over several models and the Freundlich isotherm model outperforms the Langmuir model by 5%. And bentonite clay adsorbs better due to iron oxide content.

The increasing adoption of plug-in electric vehicles (PEVs) leads to negative impacts on distribution network efficiency due to the extra load added to the system. To overcome this problem, this manuscript aims to optimally integrate distributed generators (DGs) in radial distribution networks (RDNs), while including uncoordinated charging of PEVs added to the basic daily load curve with different load models. The main objectives are minimizing the network's daily energy losses, improving the daily voltage profile, and enhancing voltage stability considering various constraints like power balance, buses' voltages, and line flow. These objectives are combined using weighting factors to formulate a weighted sum multi-objective function (MOF). A very recent metaheuristic approach, namely the Walrus optimization algorithm (WO), is addressed to identify the DGs' best locations and sizes that achieve the lowest value of MOF, without violating different constraints. The proposed optimization model along with a repetitive backward/forward load flow (BFLF) method are simulated using MATLAB 2016a software. The WO-based optimization model is applied to IEEE 33-bus, 69-bus, and a real system in El-Shourok City-district number 8 (ShC-D8), Egypt. The simulation results show that the proposed optimization method significantly enhanced the performance of RDNs incorporated with PEVs in all aspects. Moreover, the proposed WO approach proved its superiority and efficiency in getting high-quality solutions for DGs' locations and ratings, compared to other programmed algorithms. [ABSTRACT FROM AUTHOR]

Interconnected transmission systems are increasingly spreading out in HV networks to enhance system efficiency, decrease reserve capacity, and improve service reliability. However, the protection of multi-terminal lines against Broken Conductor Fault (BCF) imposes significant difficulties in such networks as the conventional distance relays cannot detect BCF, as the BCF is not associated with a significant increase in current or reduction in voltage Traditionally, the earth fault relays in transmission lines may detect such fault; Nonetheless, it suffers from a long delay time. Moreover, many of the nearby earth fault relays detect the BCF causing unnecessary trips and badly affecting the system stability. In this article, a novel single-end scheme based on extracting transient features from current signals by discrete wavelet transform (DWT) is proposed for detecting BCFs in interconnected HV transmission systems. The suggested scheme unit (SSU) is capable of accurately detecting all types of BCFs and shunt high impedance faults (SHIFs). It also adaptively calculates the applied threshold values. The accurate selectivity in multi-terminal lines is achieved based on a fault directional element by analyzing transient power polarity. The SSU discriminates between internal/external faults effectively utilizing the time difference observed between the first spikes of aerial and ground modes in the current signals. Different fault scenarios have been simulated on the IEEE 9-Bus, 230 kV interconnected system. The achieved results confirm the effectiveness, robustness, and reliability of SSU in detecting correctly BCFs as well as the SHIFs within only 24.5 ms. The SSU has confirmed its capability to be implemented in interconnected systems without any requirement for communication or synchronization between the SSU installed in multi-terminal lines. [ABSTRACT FROM AUTHOR]

Background The inflammatory process involved in severe acute respiratory syndrome coronavirus 2 infection is one of great interest in understanding the pathophysiology and severity of coronavirus disease 2019 (COVID-19). This study aimed to evaluate the association of inflammatory markers with severe COVID-19. Patients and methods The data were collected from patient files admitted to two tertiary hospitals in UAE during the COVID-19 pandemic from April to July 2020. During first COVID-19 wave that hits UAE, general symptoms as well as radiographic, blood, and immunological findings were also recorded. Results The study included 320 patients. Men (84.1%) outnumbered women (15.9%). Most (73.8%) patients had no comorbidities. The patients were from several nationalities, with Indians being the majority (51.9%). Most patients (65.6%) had mild, whereas 26.6% had severe manifestations. Only 25 patients were asymptomatic. C-reactive protein level had a significant relation to COVID-19 severity. Some parameters such as lactate dehydrogenase, ferritin, D-dimer, neutrophil/lymphocyte ratio, ICU admission, and death rates as well as radiological findings in the severe group had significant differences compared with the mild and asymptomatic groups. Conclusions These data are valuable contributions to the monitoring, severity assessment, and prognosis of patients with COVID-19. [ABSTRACT FROM AUTHOR]

Optimal coordination of overcurrent relays has become a major challenge in power distribution systems due to the increasing participation of distributed generation (DG) and electric vehicle (EV) charging stations, especially vehicle-to-grid (V2G) technology. This paper proposes a novel approach for optimal coordination of directional overcurrent relays (DOCRs) to achieve the minimum operating time and obtain optimal tuning in terms of time dial setting (TDS) and pick-up current (I P) considering V2G integration. The optimization was conducted using three different Artificial Intelligence (AI) techniques: grey wolf optimization (GWO), cuckoo search (CS), and Hunger Games Search (HGS), and was performed on two systems: IEEE 33-bus system and a local grid located in El-Shorouk City–district#8 (ShC-D8), Cairo, Egypt. The proposed methodology is constructed and validated on ETAP and MATLAB software packages. The simulation results demonstrate that the proposed optimization techniques provide high dynamic performance and accurate coordination of DOCRs. The results show that HGS achieves the minimum operating time of all overcurrent relays as compared with GWO and CS. The effect of V2G integration on the coordination methodology is also considered. The proposed approach provides a significant contribution to the field of power system protection and can help improve the reliability and efficiency of power distribution systems with V2G integration. [ABSTRACT FROM AUTHOR]