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The article presents a throughput maximization approach for UAV assisted ground networks. Throughput maximization involves minimizing delay and packet loss through UAV trajectory optimization, reinforcing the congested nodes and transmission channels. The aggressive reinforcement policy is achieved by characterizing nodes, links, and overall topology through delay, loss, throughput, and distance. A position-aware graph neural network (GNN) is used for characterization, prediction, and dynamic UAV trajectory enhancement. To establish correctness, the proposed approach is validated against optimized link state routing (OLSR) driven UAV assisted ground networks. The proposed approach considerably outperforms the classical approach by demonstrating significant gains in throughput and packet delivery ratio with notable decrements in delay and packet loss. The performance analysis of the proposed approach against software-defined UAVs (U-S) and UAVs as base stations (U-B) verifies the consistency and gains in average throughput while minimizing delay and packet loss. The scalability test of the proposed approach is performed by varying data rates and the number of UAVs.

Renewable energy has become very popular in recent years. The amount of renewable generation has increased in both grid-connected and stand-alone systems. This is because it can provide clean energy in a cost-effective and environmentally friendly fashion. Among all varieties, photovoltaic (PV) is the ultimate rising star. Integration of other technologies with solar is enhancing the efficiency and reliability of the system. In this paper a fuel cell–solar photovoltaic (FC-PV)-based hybrid energy system has been proposed to meet the electrical load demand of a small community center in India. The system is developed with PV panels, fuel cell, an electrolyzer and hydrogen storage tank. Detailed mathematical modeling of this system as well as its operation algorithm have been presented. Furthermore, cost optimization has been performed to determine ratings of PV and Hydrogen system components. The objective is to minimize the levelized cost of electricity (LCOE) of this standalone system. This optimization is performed in HOMER software as well as another tool using an artificial bee colony (ABC). The results obtained by both methods have been compared in terms of cost effectiveness. It is evident from the results that for a 68 MWh/yr of electricity demand is met by the 129 kW Solar PV, 15 kW Fuel cell along with a 34 kW electrolyzer and a 20 kg hydrogen tank with a LPSP of 0.053%. The LCOE is found to be in 0.228 $/kWh. Results also show that use of more sophisticated algorithms such as ABC yields more optimized solutions than package programs, such as HOMER. Finally, operational details for FC-PV hybrid system using IEC 61850 inter-operable communication is presented. IEC 61850 information models for FC, electrolyzer, hydrogen tank were developed and relevent IEC 61850 message exchanges for energy management in FC-PV hybrid system are demonstrated.

Purpose Arsenic, a toxic metalloid in drinking water, has become a major threat for human beings and other organisms. In the present work, attempts have been made to remove arsenate from the synthetic as well as natural water of Ballia district, India by electrocoagulation method. Efforts have also been made to optimize the various parameters such as initial arsenate concentration, pH, applied voltage, processing time, and working temperature. Method Electrocoagulation is a fast, inexpensive, selective, accurate, reproducible, and eco-friendly method for arsenate removal from groundwater. The present paper describes an electrocoagulation method for arsenate removal from groundwater using iron and zinc as anode and cathode, respectively. Results The maximum removal of arsenate was 98.8% at 2.0 mg L −1 , 7.0, 3.0 V, 10.0 min, and 30°C as arsenate concentration, pH, applied voltage, processing time, and working temperature, respectively. Relative standard deviation, coefficient of determination ( r 2 ), and confidence limits were varied from 1.50% to 1.59%, 0.9996% to 0.9998%, and 96.0% to 99.0%, respectively. The treated water was clear, colorless, and odorless without any secondary contamination. The developed and validated method was applied for arsenate removal of two samples of groundwater of Ballia district, U.P., India, having 0.563 to 0.805 mg L −1 , arsenate concentrations. Conclusions The reported method is capable for the removal of arsenate completely (100% removal) from groundwater of Ballia district. There was no change in the groundwater quality after the removal of arsenate. The treated water was safe for drinking, bathing, and recreation purposes. Therefore, this method may be the choice of arsenate removal from natural groundwater.

The healthcare industry has been put to test the need to manage enormous amounts of data provided by various sources, which are renowned for providing enormous quantities of heterogeneous information. The data are collected and analyzed with different Data Analytic (DA) and machine learning algorithm approaches. Researchers, scientists, and industrialists must manage or select the best approach associated with DA in healthcare. This scientific study is based on decision analysis between the DA factors and alternatives. The information affects the whole system in a rational manner. This information is very important in healthcare sector for appropriate prediction and analysis. The evaluation discusses its benefits and presents an analytic framework. The Fuzzy Analytic Hierarchy Process (Fuzzy AHP) approach is used to address the weight of the factors. The Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) address the rank of the data analytic alternatives used in healthcare sector. The models used in the article briefly discuss the challenges of DA and approaches to address those challenges. The assorted factors of DA are capture, cleaning, storage, security, stewardship, reporting, visualization, updating, sharing, and querying. The DA alternatives include descriptive, diagnostic, predictive, prescriptive, discovery, regression, cohort and inferential analyses. The most influential factors of the DA and the most suitable approach for the DA are evaluated. The ‘cleaning’ factor has the highest weight, and ‘updating’ is achieved at least by the Fuzzy-AHP approach. The regression approach of data analysis had the highest rank, and the diagnostic analysis had the lowest rank. Decision analyses are necessary for data scientists and medical providers to predict diseases appropriately in the healthcare domain. This analysis also revealed the cost benefits to hospitals.

Removal of arsenite from aqueous solution was carried out using electro-coagulation method. The experiments were conducted using copper-copper and zinc-zinc electrodes. The optimized experimental parameters were 2.0 mg/L initial concentration, 16.0-min processing time, 6.0 pH, 3.0-V applied voltage and 30 °C temperature for zinc-zinc electrodes while these values for copper-copper electrodes were 2.0 mg/L initial concentration, 20.0-min processing time, 7.0 pH, 5.0-V applied voltage and 30 °C temperature. The results demonstrated that zinc-zinc and copper-copper electrodes removed arsenite up to 99.89 and 99.56 %, respectively. The treated water was clear, colorless and odorless without any secondary contamination. There was no change in water quality after the removal of arsenite. The reported method is capable to remove arsenite from water at 6-7 pH range, which is a pH range of natural water. Therefore, this method may be the choice of arsenite removal from natural ground water.

Kikuchi–Fujimoto disease (KFD) is a rare benign and self-limiting syndrome. We aim to review cases of KFD at our institution as a rare illness in the Arab ethnic descent and to analyse reports from most countries in the East Mediterranean zone. This is a retrospective study in which the histopathology database was searched for the diagnosis of KFD. A full review of KFD patients’ medical records was done. Data regarding demographic features, clinical presentation, laboratory findings, comorbidities, and management protocols were obtained. Published KFD cases from east Mediterranean countries were discussed and compared to other parts of the world. Out of 1968 lymph node biopsies studied, 11 (0.6%) cases of KFD were identified. The mean age of patients with KFD was 32 years (4–59). 73% (8/11) were females. The disease was self-limiting in 5 patients (45%); corticosteroid therapy was needed in 4 patients (34%). One patient was treated with methotrexate and one with antibiotics. One patient died as a consequence of lymphoma. Jordanians and Mediterranean populations, especially those of Arab ethnic background, seem to have low rates of KFD. The genetic susceptibility theory may help to explain the significantly higher disease prevalence among East Asians. Early diagnosis of KFD—although challenging—is essential to reduce the morbidity related to this illness.

Let S = ℤp[u, v]/〈u2, v2, uv − uv〉 be a semi-local ring, where p is a prime number. In the present article, we determine the generating sets of S and use them to construct the structures of ℤpS-additive cyclic and constacyclic codes. The minimal polynomials and spanning sets of ℤpS-additive cyclic and constacyclic codes are also determined. These codes are identified as S[y]-submodules of the ring Sβ1, β2 = ℤp[y]/〈yβ1 − 1〉 × S[y]/〈yβ2 − 1〉. Some results that represent the relationship between the minimal polynomials of ℤpS-additive cyclic codes and their duals have been obtained. Furthermore, optimal ℤpS-additive codes and maximum distance separable codes have been evaluated (see Table 1). Finally, we use MAGMA software to find the parameters of Optimal and MDSS codes.

Communication plays a key role in the effective management of virtual power plants (VPPs). For effective and stable operation of VPPs, a reliable, secure, and standardized communication infrastructure is required. In the literature, efforts were made to develop this based on industry standards, such as the IEC 60870-5-104, OpenADR 2.0b and IEC 61850. Due to its global acceptance and strong object-oriented information models, IEC 61850 standard-based communication is preferred for smart grid operations, including VPPs. However, communication models based on IEC 61850 present cybersecurity and scalability challenges. To address this issue, this paper presents an eXtensible Message Presence Protocol (XMPP)-based IEC 61850 communication for VPPs. Firstly, a full mapping of IEC 61850 messages for VPP energy management is carried out. Secondly, XMPP-based single- and multiple-domain communications are demonstrated. Finally, a federation concept has been added to facilitate communication in multi-domain communication networks. These models show that a standard communication model can be implemented with IEC 61850 and XMPP, not only for VPPs but other wide-area communication implementations in smart grids. This not only facilitates plug-and-play (PnP) with easy component additions but secures smart grid communication against cyber-attacks.

Environmental problems with chemical and biological water pollution have become a major concern for society. Providing people with safe and affordable water is a grand challenge of the 21st century. The study investigates the photocatalytic degradation capabilities of hydrothermally prepared pure and Cu-doped ZnO nanoparticles (NPs) for the elimination of dye pollutants. A simple, cost-effective hydrothermal process is employed to synthesize the Cu-doped ZnO NPs. The photocatalytic dye degradation activity of the synthesized Cu-doped ZnO NPs is tested by using methylene blue (MB) dye. In addition, the parameters that affect photodegradation efficiency, such as catalyst concentration, starting potential of hydrogen (pH), and dye concentration, were also assessed. The dye degradation is found to be directly proportional to the irradiation time, as 94% of the MB dye is degraded in 2 hrs. Similarly, the dye degradation shows an inverse relation to the MB dye concentration, as the degradation reduced from 94% to 20% when the MB concentration increases from 5 ppm to 80 ppm. The synthesized cost-effective and environmentally friendly Cu-doped ZnO NPs exhibit improved photocatalytic activity against MB dye and can therefore be employed in wastewater treatment materials.